music research articles

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• BJPsych Int
• v.14(2); 2017 May

Music and the brain: the neuroscience of music and musical appreciation

Michael trimble.

1 Institute of Neurology, University College London, UK, email ku.ca.lcu.noi@elbmirtm

Dale Hesdorffer

2 Gertrude H. Sergievsky Center and Department of Epidemilogy, Columbia University, New York City, USA

Through music we can learn much about our human origins and the human brain. Music is a potential method of therapy and a means of accessing and stimulating specific cerebral circuits. There is also an association between musical creativity and psychopathology. This paper provides a brief review.

Art history is the unfolding of subjectivity…. (T. Adorno)

An evolutionary perspective

There have been many attempts to identify behaviours which reliably distinguish our species, Homo sapiens , from our closest living cousins. Ascribed activities, from tool-making to having a theory of mind and empathy, have been rejected, as observations of anthropologists and ethnologists continue to emphasise similarities rather than differences placing us within the great chain of beings. There can be no doubt about the greater development of our cognitive attributes, linked closely with the evolutionary developments of our brain, in terms of both size and structure. Bipedalism, the use of fire, the development of effective working memory and our vocal language efficient communication have all emerged from these genetic–environmental adaptations over several million years (Pasternak, 2007 ).

Two features of our world which are universal and arguably have been a feature of an earlier evolutionary development are our ability to create and respond to music, and to dance to the beat of time.

Somewhere along the evolutionary way, our ancestors, with very limited language but with considerable emotional expression, began to articulate and gesticulate feelings: denotation before connotation. But, as the philosopher Susanne Langer noted, ‘The most highly developed type of such purely connotational semantic is music’ (Langer, 1951 , p. 93). In other words, meaning in music came to us before meaning given by words.

The mammalian middle ear developed from the jaw bones of earlier reptiles and carries sound at only specific frequencies. It is naturally attuned to the sound of the human voice, although has a range greater than that required for speech. Further, the frequency band which mothers use to sing to their babies, and so-called motherese or child-directed speech, with exaggerated intonation and rhythm, corresponds to that which composers have traditionally used in their melodies. In the same way that there is a limited sensitive period in which the infant can learn language and learn to respond to spoken language, there must be a similar phase of brain development for the incorporation of music.

One of the differences between the developed brains of Homo sapiens and those of the great apes is the increase in area allocated to processing auditory information. Thus, in other primates the size of the visual cortex correlates well with brain size, but in Homo sapiens it is smaller. In contrast, increases in size elsewhere in the human brain have occurred, notably in the temporal lobes, especially the dorsal area that relates to the auditory reception of speech. The expansion of primary and association auditory cortices and their connections, associated with the increased size of the cerebellum and areas of prefrontal and premotor cortex linked through basal ganglia structures, heralded a shift to an aesthetics based on sound, and to abilities to entrain to external rhythmic inputs. The first musical instrument used by our ancestors was the voice. The ear is always open and, unlike vision and the eyes or the gaze, sound cannot readily be averted. From the rhythmic beating within and with the mother’s body for the fetus and young infant, to the primitive drum-like beating of sticks on wood and hand clapping of our adolescent and adult proto-speaking ancestors, the growing infant is surrounded by and responds to rhythm. But, as Langer ( 1951 , p. 93) put it, ‘being more variable than the drum, voices soon made patterns and the long endearing melodies of primitive song became a part of communal celebration’. Some support for these ideas comes from the work of Mithen, who has argued that spoken language and music evolved from a proto-language, a musi-language which stemmed from primate calls and was used by the Neanderthals; it was emotional but without words as we know them (Mithen, 2005 ).

The suggestion is that our language of today emerged via a proto-language, driven by gesture, framed by musicality and performed by the flexibility which accrued with expanded anatomical developments, not only of the brain, but also of the coordination of our facial, pharyngeal and laryngeal muscles. Around the same time (with a precision of many thousands of years), the bicameral brain, although remaining bipartite, with the two cooperating cerebral hemispheres coordinating life for the individual in cohesion with the surrounding environment, became differently balanced with regard to the functions of the two sides: pointing and proposition (left) as opposed to urging and yearning (right) (Trimble, 2012 ).

The experience of music

A highly significant finding to emerge from the studies of the effects in the brain of listening to music is the emphasis on the importance of the right (non-dominant) hemisphere. Thus, lesions following cerebral damage lead to impairments of appreciation of pitch, timbre and rhythm (Stewart et al , 2006 ) and studies using brain imaging have shown that the right hemisphere is preferentially activated when listening to music in relation to the emotional experience, and that even imagining music activates areas on this side of the brain (Blood et al , 1999 ). This should not be taken to imply that there is a simple left–right dichotomy of functions in the human brain. However, it is the case that traditional neurology has to a large extent ignored the talents of the non-dominant hemisphere, much in favour of the dominant (normally left) hemisphere. In part this stems from an overemphasis on the role of the latter in propositional language and a lack of interest in the emotional intonations of speech (prosody) that give so much meaning to expression.

The link between music and emotion seems to have been accepted for all time. Plato considered that music played in different modes would arouse different emotions, and as a generality most of us would agree on the emotional significance of any particular piece of music, whether it be happy or sad; for example, major chords are perceived to be cheerful, minor ones sad. The tempo or movement in time is another component of this, slower music seeming less joyful than faster rhythms. This reminds us that even the word motion is a significant part of e motion , and that in the dance we are moving – as we are moved emotionally by music.

Until recently, musical theorists had largely concerned themselves with the grammar and syntax of music rather than with the affective experiences that arise in response to music. Music, if it does anything, arouses feelings and associated physiological responses, and these can now be measured. For the ordinary listener, however, there may be no necessary relationship of the emotion to the form and content of the musical work, since ‘the real stimulus is not the progressive unfolding of the musical structure but the subjective content of the listener’s mind’ (Langer, 1951 , p. 258). Such a phenomenological approach directly contradicts the empirical techniques of so much current neuroscience in this area, yet is of direct concern to psychiatry, and topics such as compositional creativity.

If it is a language, music is a language of feeling. Musical rhythms are life rhythms, and music with tensions, resolutions, crescendos and diminuendos, major and minor keys, delays and silent interludes, with a temporal unfolding of events, does not present us with a logical language, but, to quote Langer again, it ‘ reveals the nature of feelings with a detail and truth that language cannot approach’ (Langer, 1951 , p. 199, original emphasis).

This idea seems difficult for a philosophical mind to follow, namely that there can be knowledge without words. Indeed, the problem of describing a ‘language’ of feeling permeates the whole area of philosophy and neuroscience research, and highlights the relative futility of trying to classify our emotions – ‘Music is revealing, where words are obscuring’ (Langer, 1951 , p. 206).

Musical ability and psychiatric disorder

There is an extensive literature attesting to some associations between creativity and psychopathology (Trimble, 2007 ). The links seem to vary with different kinds of high achievement, and mood disorders are over-represented. Although samples of creative people have a significant excess of cyclothymia and bipolarity, florid manic–depressive illness is relatively uncommon. Biographies of famous musicians are of considerable interest in exploring brain–behaviour associations. Attempts to transform descriptions of people from biographies into specific DSM diagnoses cannot achieve high levels of validity and reliability, since lack of autobiographical materials and reliable contemporary medical accounts makes any diagnostic formulation necessarily tentative. However, with regard to classical composers within the Western canon, it must be of considerable significance that there are so many who seem to have suffered from affective disorders, the incidence of mood disorders ranging between 35% and 40% (Mula & Trimble, 2009 ). It is possible that similar associations occur in non-Western composers, although studies have not been published. In contrast, none seems to have had schizophrenia. These results have importance in understanding the structure and function of the human brain, and suggest avenues for therapeutic investigation which will vary with diagnosis.

Music therapy

Music provides and provokes a response, which is universal, ingrained into our evolutionary development, and leads to marked changes in emotions and movement. The anatomical associations noted above suggest that music must be viewed as one way to stimulate the brain. Music provides a non-invasive technique, which has attracted much interest but little empirical exploration to date. The therapeutic value of music can be in part explained by its cultural role in facilitating social learning and emotional well-being. However, a number of studies have shown that rhythmic entrainment of motor function can actively facilitate the recovery of movement in patients with stroke, Parkinson’s disease, cerebral palsy and traumatic brain injury (Thaut, 2005 ). Studies of people with memory disorders, such as Alzheimer’s disease, suggest that neuronal memory traces built through music are deeply ingrained and more resilient to neurodegenerative influences. Findings from individual randomised trials suggest that music therapy is accepted by people with depression and is associated with improvements in mood disorders (Maratos et al , 2008 ). Further, the potential applications of music therapy in patients with neuropsychiatric disorders, including autism spectrum disorders, albeit intuitive, have led to psychotherapeutic uses aimed at directly evoking emotions.

Evidence suggests that music can decrease seizure frequency, stop refractory status epilepticus and decrease electroencephalographic spike frequency in children with epilepsy in awake and sleep states. We know that many people with epilepsy have electroencephalographic abnormalities and, in some people, these can be ‘normalised’ by music. In addition to the need for trials of musical interventions in epilepsy, we should also consider whether the results of sonification of an electroencephalogram, which directly reflects the time course of cerebral rhythms, may be used to entrain ‘normal’ brain rhythms in people with seizure disorders. Alteration of the electroencephalogram via biofeedback of different components of sonified electroencephalography, or modulation of the musical input to a stimulus that affects the emotional state of the patient and hence cerebral and limbic activity and cerebral rhythms, are therapeutic possibilities which are currently being investigated (Bodner et al , 2012 ).

These data suggest that the effects and cost-effectiveness of music therapy in patients with neuropsychiatric disorders should be further explored. To date, most work has been done with Western-style compositions, and the well structured music of Mozart and Bach has been a popular basis for interventions. The following paper by Shantala Hegde notes the potential of other musical styles as therapy. Through music we learn much about our human origins and the human brain, and have a potential method of therapy by accessing and stimulating specific cerebral circuits.

• Blood, A. J., Zatorre, R. J., Bermudez, P., et al. (1999) Emotional responses to pleasant and unpleasant music correlate with activity in paralimbic brain regions . Nature Neuroscience , 2 , 382–387. [ PubMed ] [ Google Scholar ]
• Bodner, M., Turner, R. P., Schwacke, J., et al. (2012) Reduction of seizure occurrence from exposures to auditory stimulation in individuals with neurological handicaps: a randomized controlled trial . PLoS One , 7 , e45303. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Langer, S. K. (1951) Philosophy in a New Key . Harvard University Press. [ Google Scholar ]
• Maratos, A. S., Gold, C., Wang, X., et al. (2008) Music therapy for depression . Cochrane Database of Systematic Reviews , ( 1 ), CD004517. [ PubMed ] [ Google Scholar ]
• Mithen, S. (2005) The Singing Neanderthals . Weidenfeld and Nicholson. [ Google Scholar ]
• Mula, M. & Trimble, M. R. (2009) Music and madness: neuropsychiatric aspects of music . Clinical Medicine , 9 , 83–86. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Pasternak, C. (2007) What Makes Us Human . One World. [ Google Scholar ]
• Stewart, L., von Kriegstein, K. & Warren, J. D. (2006) Music and the brain: disorders of musical listening . Brain , 129 , 2533–2553. [ PubMed ] [ Google Scholar ]
• Thaut, M. H. (2005) The future of music in therapy and medicine . Annals of the New York Academy of Science , 1060 , 303–308. [ PubMed ] [ Google Scholar ]
• Trimble, M. R. (2007) The Soul in the Brain: The Cerebral Basis of Language, Art and Belief . Johns Hopkins University Press. [ Google Scholar ]
• Trimble, M. R. (2012) Why Humans Like to Cry. Tragedy, Evolution and the Brain . Oxford University Press. [ Google Scholar ]

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Review Article
• Published: 29 March 2022

Music in the brain

• Peter Vuust   ORCID: orcid.org/0000-0002-4908-735X 1 ,
• Ole A. Heggli   ORCID: orcid.org/0000-0002-7461-0309 1 ,
• Karl J. Friston   ORCID: orcid.org/0000-0001-7984-8909 2 &
• Morten L. Kringelbach   ORCID: orcid.org/0000-0002-3908-6898 1 , 3 , 4  

Nature Reviews Neuroscience volume  23 ,  pages 287–305 ( 2022 ) Cite this article

25k Accesses

93 Citations

278 Altmetric

Metrics details

• Neuroscience

Music is ubiquitous across human cultures — as a source of affective and pleasurable experience, moving us both physically and emotionally — and learning to play music shapes both brain structure and brain function. Music processing in the brain — namely, the perception of melody, harmony and rhythm — has traditionally been studied as an auditory phenomenon using passive listening paradigms. However, when listening to music, we actively generate predictions about what is likely to happen next. This enactive aspect has led to a more comprehensive understanding of music processing involving brain structures implicated in action, emotion and learning. Here we review the cognitive neuroscience literature of music perception. We show that music perception, action, emotion and learning all rest on the human brain’s fundamental capacity for prediction — as formulated by the predictive coding of music model. This Review elucidates how this formulation of music perception and expertise in individuals can be extended to account for the dynamics and underlying brain mechanisms of collective music making. This in turn has important implications for human creativity as evinced by music improvisation. These recent advances shed new light on what makes music meaningful from a neuroscientific perspective.

This is a preview of subscription content, access via your institution

Access options

Access Nature and 54 other Nature Portfolio journals

Get Nature+, our best-value online-access subscription

24,99 € / 30 days

cancel any time

Subscribe to this journal

Receive 12 print issues and online access

176,64 € per year

only 14,72 € per issue

Buy this article

• Purchase on Springer Link
• Instant access to full article PDF

Prices may be subject to local taxes which are calculated during checkout

Similar content being viewed by others

Universality, domain-specificity and development of psychological responses to music

Manvir Singh & Samuel A. Mehr

Scaling behaviour in music and cortical dynamics interplay to mediate music listening pleasure

Ana Filipa Teixeira Borges, Mona Irrmischer, … Klaus Linkenkaer-Hansen

An ALE meta-analytic review of top-down and bottom-up processing of music in the brain

Victor Pando-Naude, Agata Patyczek, … Peter Vuust

Zatorre, R. J., Chen, J. L. & Penhune, V. B. When the brain plays music: auditory–motor interactions in music perception and production. Nat. Rev. Neurosci. 8 , 547–558 (2007). A seminal review of auditory–motor coupling in music .

Article   CAS   PubMed   Google Scholar  

Koelsch, S. Toward a neural basis of music perception–a review and updated model. Front. Psychol. 2 , 110 (2011).

Article   PubMed   PubMed Central   Google Scholar  

Maes, P. J., Leman, M., Palmer, C. & Wanderley, M. M. Action-based effects on music perception. Front. Psychol. 4 , 1008 (2014).

Koelsch, S. Brain correlates of music-evoked emotions. Nat. Rev. Neurosci. 15 , 170–180 (2014). In this review, the author shows how music engages phylogenetically old reward networks in the brain to evoke emotions, and not merely subjective feelings .

Vuust, P. & Witek, M. A. Rhythmic complexity and predictive coding: a novel approach to modeling rhythm and meter perception in music. Front. Psychol. 5 , 1111 (2014).

Friston, K. The free-energy principle: a unified brain theory? Nat. Rev. Neurosci. 11 , 127–138 (2010). This review posits that several global brain theories may be unified by the free-energy principle .

Koelsch, S., Vuust, P. & Friston, K. Predictive processes and the peculiar case of music. Trends Cogn. Sci. 23 , 63–77 (2019). This review focuses specifically on predictive coding in music .

Article   PubMed   Google Scholar  

Meyer, L. Emotion and Meaning in Music (Univ. of Chicago Press, 1956).

Lerdahl, F. & Jackendoff, R. A Generative Theory of Music (MIT Press, 1999).

Huron, D. Sweet Anticipation (MIT Press, 2006). In this book, Huron draws on evolutionary theory and statistical learning to propose a general theory of musical expectation .

Hansen, N. C. & Pearce, M. T. Predictive uncertainty in auditory sequence processing. Front. Psychol. https://doi.org/10.3389/fpsyg.2013.01008 (2014).

Vuust, P., Brattico, E., Seppanen, M., Naatanen, R. & Tervaniemi, M. The sound of music: differentiating musicians using a fast, musical multi-feature mismatch negativity paradigm. Neuropsychologia 50 , 1432–1443 (2012).

Altenmüller, E. O. How many music centers are in the brain? Ann. N. Y. Acad. Sci. 930 , 273–280 (2001).

Monelle, R. Linguistics and Semiotics in Music (Harwood Academic Publishers, 1992).

Rohrmeier, M. A. & Koelsch, S. Predictive information processing in music cognition. A critical review. Int. J. Psychophysiol. 83 , 164–175 (2012).

Vuust, P., Dietz, M. J., Witek, M. & Kringelbach, M. L. Now you hear it: a predictive coding model for understanding rhythmic incongruity. Ann. N. Y. Acad. Sci. https://doi.org/10.1111/nyas.13622 (2018).

Vuust, P., Ostergaard, L., Pallesen, K. J., Bailey, C. & Roepstorff, A. Predictive coding of music–brain responses to rhythmic incongruity. Cortex 45 , 80–92 (2009).

Vuust, P. & Frith, C. Anticipation is the key to understanding music and the effects of music on emotion. Behav. Brain Res. 31 , 599–600 (2008). This is the foundation for the PCM model used in this Review .

Google Scholar  

Garrido, M. I., Sahani, M. & Dolan, R. J. Outlier responses reflect sensitivity to statistical structure in the human brain. PLoS Comput. Biol. 9 , e1002999 (2013).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Lumaca, M., Baggio, G., Brattico, E., Haumann, N. T. & Vuust, P. From random to regular: neural constraints on the emergence of isochronous rhythm during cultural transmission. Soc. Cogn. Affect. Neurosci. 13 , 877–888 (2018).

Quiroga-Martinez, D. R. et al. Musical prediction error responses similarly reduced by predictive uncertainty in musicians and non-musicians. Eur. J. Neurosci. https://doi.org/10.1111/ejn.14667 (2019).

Article   Google Scholar  

Koelsch, S., Schröger, E. & Gunter, T. C. Music matters: preattentive musicality of the human brain. Psychophysiology 39 , 38–48 (2002).

Koelsch, S., Schmidt, B.-h & Kansok, J. Effects of musical expertise on the early right anterior negativity: an event-related brain potential study. Psychophysiology 39 , 657–663 (2002).

Lumaca, M., Dietz, M. J., Hansen, N. C., Quiroga-Martinez, D. R. & Vuust, P. Perceptual learning of tone patterns changes the effective connectivity between Heschl’s gyrus and planum temporale. Hum. Brain Mapp. 42 , 941–952 (2020).

Lieder, F., Daunizeau, J., Garrido, M. I., Friston, K. J. & Stephan, K. E. Modelling trial-by-trial changes in the mismatch negativity. PLoS Comput. Biol. 9 , e1002911 (2013).

Wacongne, C., Changeux, J. P. & Dehaene, S. A neuronal model of predictive coding accounting for the mismatch negativity. J. Neurosci. 32 , 3665–3678 (2012).

Kiebel, S. J., Garrido, M. I. & Friston, K. J. Dynamic causal modelling of evoked responses: the role of intrinsic connections. Neuroimage 36 , 332–345 (2007).

Feldman, H. & Friston, K. J. Attention, uncertainty, and free-energy. Front. Hum. Neurosci. 4 , 215 (2010).

Cheung, V. K. M. et al. Uncertainty and surprise jointly predict musical pleasure and amygdala, hippocampus, and auditory cortex activity. Curr. Biol. 29 , 4084–4092 e4084 (2019). This fMRI study ties uncertainty and surprise to musical pleasure .

McDermott, J. H. & Oxenham, A. J. Music perception, pitch, and the auditory system. Curr. Opin. Neurobiol. 18 , 452–463 (2008).

Thoret, E., Caramiaux, B., Depalle, P. & McAdams, S. Learning metrics on spectrotemporal modulations reveals the perception of musical instrument timbre. Nat. Hum. Behav. 5 , 369–377 (2020).

Siedenburg, K. & McAdams, S. Four distinctions for the auditory “wastebasket” of timbre. Front. Psychol. 8 , 1747 (2017).

Bendor, D. & Wang, X. The neuronal representation of pitch in primate auditory cortex. Nature 436 , 1161–1165 (2005).

Zatorre, R. J. Pitch perception of complex tones and human temporal-lobe function. J. Acoustical Soc. Am. 84 , 566–572 (1988).

Article   CAS   Google Scholar  

Warren, J. D., Uppenkamp, S., Patterson, R. D. & Griffiths, T. D. Separating pitch chroma and pitch height in the human brain. Proc. Natl Acad. Sci. USA 100 , 10038–10042 (2003). Using fMRI data, this study shows that pitch chroma is represented anterior to the primary auditory cortex, and pitch height is represented posterior to the primary auditory cortex .

Rauschecker, J. P. & Scott, S. K. Maps and streams in the auditory cortex: nonhuman primates illuminate human speech processing. Nat. Neurosci. 12 , 718–724 (2009).

Leaver, A. M., Van Lare, J., Zielinski, B., Halpern, A. R. & Rauschecker, J. P. Brain activation during anticipation of sound sequences. J. Neurosci. 29 , 2477–2485 (2009).

Houde, J. F. & Chang, E. F. The cortical computations underlying feedback control in vocal production. Curr. Opin. Neurobiol. 33 , 174–181 (2015).

Lee, Y. S., Janata, P., Frost, C., Hanke, M. & Granger, R. Investigation of melodic contour processing in the brain using multivariate pattern-based fMRI. Neuroimage 57 , 293–300 (2011).

Janata, P. et al. The cortical topography of tonal structures underlying Western music. Science 298 , 2167–2170 (2002).

Saffran, J. R., Aslin, R. N. & Newport, E. L. Statistical learning by 8-month-old infants. Science 274 , 1926–1928 (1996).

Saffran, J. R., Johnson, E. K., Aslin, R. N. & Newport, E. L. Statistical learning of tone sequences by human infants and adults. Cognition 70 , 27–52 (1999).

Krumhansl, C. L. Perceptual structures for tonal music. Music. Percept. 1 , 28–62 (1983).

Margulis, E. H. A model of melodic expectation. Music. Percept. 22 , 663–714 (2005).

Temperley, D. A probabilistic model of melody perception. Cogn. Sci. 32 , 418–444 (2008).

Pearce, M. T. & Wiggins, G. A. Auditory expectation: the information dynamics of music perception and cognition. Top. Cogn. Sci. 4 , 625–652 (2012).

Sears, D. R. W., Pearce, M. T., Caplin, W. E. & McAdams, S. Simulating melodic and harmonic expectations for tonal cadences using probabilistic models. J. N. Music. Res. 47 , 29–52 (2018).

Näätänen, R., Gaillard, A. W. & Mäntysalo, S. Early selective-attention effect on evoked potential reinterpreted. Acta Psychol. 42 , 313–329 (1978).

Näätänen, R., Paavilainen, P., Rinne, T. & Alho, K. The mismatch negativity (MMN) in basic research of central auditory processing: a review. Clin. Neurophysiol. 118 , 2544–2590 (2007). This classic review covers three decades of MMN research to understand auditory perception .

Wallentin, M., Nielsen, A. H., Friis-Olivarius, M., Vuust, C. & Vuust, P. The Musical Ear Test, a new reliable test for measuring musical competence. Learn. Individ. Differ. 20 , 188–196 (2010).

Tervaniemi, M. et al. Top-down modulation of auditory processing: effects of sound context, musical expertise and attentional focus. Eur. J. Neurosci. 30 , 1636–1642 (2009).

Burunat, I. et al. The reliability of continuous brain responses during naturalistic listening to music. Neuroimage 124 , 224–231 (2016).

Burunat, I. et al. Action in perception: prominent visuo-motor functional symmetry in musicians during music listening. PLoS ONE 10 , e0138238 (2015).

Article   PubMed   PubMed Central   CAS   Google Scholar  

Alluri, V. et al. Large-scale brain networks emerge from dynamic processing of musical timbre, key and rhythm. Neuroimage 59 , 3677–3689 (2012). A free-listening fMRI study showing brain networks involved in perception of distinct acoustical features of music .

Halpern, A. R. & Zatorre, R. J. When that tune runs through your head: a PET investigation of auditory imagery for familiar melodies. Cereb. Cortex 9 , 697–704 (1999).

Herholz, S. C., Halpern, A. R. & Zatorre, R. J. Neuronal correlates of perception, imagery, and memory for familiar tunes. J. Cogn. Neurosci. 24 , 1382–1397 (2012).

Pallesen, K. J. et al. Emotion processing of major, minor, and dissonant chords: a functional magnetic resonance imaging study. Ann. N. Y. Acad. Sci. 1060 , 450–453 (2005).

McPherson, M. J. et al. Perceptual fusion of musical notes by native Amazonians suggests universal representations of musical intervals. Nat. Commun. 11 , 2786 (2020).

Helmholtz H. L. F. On the Sensations of Tone as a Physiological Basis for the Theory of Music (Cambridge Univ. Press, 1954).

Vassilakis, P. N. & Kendall, R. A. in Human Vision and Electronic Imaging XV . 75270O (International Society for Optics and Photonics, 2010).

Plomp, R. & Levelt, W. J. M. Tonal consonance and critical bandwidth. J. Acoustical Soc. Am. 38 , 548–560 (1965).

McDermott, J. H., Schultz, A. F., Undurraga, E. A. & Godoy, R. A. Indifference to dissonance in native Amazonians reveals cultural variation in music perception. Nature 535 , 547–550 (2016). An ethnomusicology study showing that consonance preference may be absent in people with minimal exposure to Western music .

Mehr, S. A. et al. Universality and diversity in human song. Science https://doi.org/10.1126/science.aax0868 (2019).

Patel, A. D., Gibson, E., Ratner, J., Besson, M. & Holcomb, P. J. Processing syntactic relations in language and music: an event-related potential study. J. Cogn. Neurosci. 10 , 717–733 (1998). This classic study compares responses to syntactic incongruities in both language and Western tonal music .

Janata, P. The neural architecture of music-evoked autobiographical memories. Cereb. Cortex 19 , 2579–2594 (2009).

Maess, B., Koelsch, S., Gunter, T. C. & Friederici, A. D. Musical syntax is processed in Broca’s area: an MEG study. Nat. Neurosci. 4 , 540–545 (2001).

Koelsch, S. et al. Differentiating ERAN and MMN: an ERP study. Neuroreport 12 , 1385–1389 (2001). Using EEG, the authors show that ERAN and MMN reflect different cognitive mechanisms .

Loui, P., Grent-‘t-Jong, T., Torpey, D. & Woldorff, M. Effects of attention on the neural processing of harmonic syntax in Western music. Cogn. Brain Res. 25 , 678–687 (2005).

Koelsch, S., Fritz, T., Schulze, K., Alsop, D. & Schlaug, G. Adults and children processing music: an fMRI study. Neuroimage 25 , 1068–1076 (2005).

Tillmann, B., Janata, P. & Bharucha, J. J. Activation of the inferior frontal cortex in musical priming. Ann. N. Y. Acad. Sci. 999 , 209–211 (2003).

Garza-Villarreal, E. A., Brattico, E., Leino, S., Ostergaard, L. & Vuust, P. Distinct neural responses to chord violations: a multiple source analysis study. Brain Res. 1389 , 103–114 (2011).

Leino, S., Brattico, E., Tervaniemi, M. & Vuust, P. Representation of harmony rules in the human brain: further evidence from event-related potentials. Brain Res. 1142 , 169–177 (2007).

Sammler, D. et al. Co-localizing linguistic and musical syntax with intracranial EEG. Neuroimage 64 , 134–146 (2013).

Loui, P., Wessel, D. L. & Hudson Kam, C. L. Humans rapidly learn grammatical structure in a new musical scale. Music. Percept. 27 , 377–388 (2010).

Loui, P., Wu, E. H., Wessel, D. L. & Knight, R. T. A generalized mechanism for perception of pitch patterns. J. Neurosci. 29 , 454–459 (2009).

Cheung, V. K. M., Meyer, L., Friederici, A. D. & Koelsch, S. The right inferior frontal gyrus processes nested non-local dependencies in music. Sci. Rep. 8 , 3822 (2018).

Haueisen, J. & Knosche, T. R. Involuntary motor activity in pianists evoked by music perception. J. Cogn. Neurosci. 13 , 786–792 (2001).

Bangert, M. et al. Shared networks for auditory and motor processing in professional pianists: evidence from fMRI conjunction. Neuroimage 30 , 917–926 (2006).

Baumann, S. et al. A network for audio-motor coordination in skilled pianists and non-musicians. Brain Res. 1161 , 65–78 (2007).

Lahav, A., Saltzman, E. & Schlaug, G. Action representation of sound: audiomotor recognition network while listening to newly acquired actions. J. Neurosci. 27 , 308–314 (2007).

Bianco, R. et al. Neural networks for harmonic structure in music perception and action. Neuroimage 142 , 454–464 (2016).

Eerola, T., Vuoskoski, J. K., Peltola, H.-R., Putkinen, V. & Schäfer, K. An integrative review of the enjoyment of sadness associated with music. Phys. Life Rev. 25 , 100–121 (2018).

Huron, D. M. D. The harmonic minor scale provides an optimum way of reducing average melodic interval size, consistent with sad affect cues. Empir. Musicol. Rev. 7 , 15 (2012).

Huron, D. A comparison of average pitch height and interval size in major-and minor-key themes: evidence consistent with affect-related pitch prosody. 3 , 59-63 (2008).

Juslin, P. N. & Laukka, P. Communication of emotions in vocal expression and music performance: different channels, same code? Psychol. Bull. 129 , 770 (2003).

Fritz, T. et al. Universal recognition of three basic emotions in music. Curr. Biol. 19 , 573–576 (2009).

London, J. Hearing in Time: Psychological Aspects of Musical Meter (Oxford Univ. Press, 2012).

Honing, H. Without it no music: beat induction as a fundamental musical trait. Ann. N. Y. Acad. Sci. 1252 , 85–91 (2012).

Hickok, G., Farahbod, H. & Saberi, K. The rhythm of perception: entrainment to acoustic rhythms induces subsequent perceptual oscillation. Psychol. Sci. 26 , 1006–1013 (2015).

Yabe, H., Tervaniemi, M., Reinikainen, K. & Näätänen, R. Temporal window of integration revealed by MMN to sound omission. Neuroreport 8 , 1971–1974 (1997).

Andreou, L.-V., Griffiths, T. D. & Chait, M. Sensitivity to the temporal structure of rapid sound sequences — an MEG study. Neuroimage 110 , 194–204 (2015).

Jongsma, M. L., Meeuwissen, E., Vos, P. G. & Maes, R. Rhythm perception: speeding up or slowing down affects different subcomponents of the ERP P3 complex. Biol. Psychol. 75 , 219–228 (2007).

Graber, E. & Fujioka, T. Endogenous expectations for sequence continuation after auditory beat accelerations and decelerations revealed by P3a and induced beta-band responses. Neuroscience 413 , 11–21 (2019).

Brochard, R., Abecasis, D., Potter, D., Ragot, R. & Drake, C. The “ticktock” of our internal clock: direct brain evidence of subjective accents in isochronous sequences. Psychol. Sci. 14 , 362–366 (2003).

Lerdahl, F. & Jackendoff, R. An overview of hierarchical structure in music. Music. Percept. 1 , 229–252 (1983).

Large, E. W. & Kolen, J. F. Resonance and the perception of musical meter. Connect. Sci. 6 , 177–208 (1994).

Large, E. W. & Jones, M. R. The dynamics of attending: how people track time-varying events. Psychol. Rev. 106 , 119–159 (1999).

Cutietta, R. A. & Booth, G. D. The influence of metre, mode, interval type and contour in repeated melodic free-recall. Psychol. Music 24 , 222–236 (1996).

Smith, K. C. & Cuddy, L. L. Effects of metric and harmonic rhythm on the detection of pitch alterations in melodic sequences. J. Exp. Psychol. 15 , 457–471 (1989).

CAS   Google Scholar  

Palmer, C. & Krumhansl, C. L. Mental representations for musical meter. J. Exp. Psychol. 16 , 728–741 (1990).

Einarson, K. M. & Trainor, L. J. Hearing the beat: young children’s perceptual sensitivity to beat alignment varies according to metric structure. Music. Percept. 34 , 56–70 (2016).

Large, E. W., Herrera, J. A. & Velasco, M. J. Neural networks for beat perception in musical rhythm. Front. Syst. Neurosci. 9 , 159 (2015).

Nozaradan, S., Peretz, I., Missal, M. & Mouraux, A. Tagging the neuronal entrainment to beat and meter. J. Neurosci. 31 , 10234–10240 (2011).

Nozaradan, S., Peretz, I. & Mouraux, A. Selective neuronal entrainment to the beat and meter embedded in a musical rhythm. J. Neurosci. 32 , 17572–17581 (2012).

Nozaradan, S., Schonwiesner, M., Keller, P. E., Lenc, T. & Lehmann, A. Neural bases of rhythmic entrainment in humans: critical transformation between cortical and lower-level representations of auditory rhythm. Eur. J. Neurosci. 47 , 321–332 (2018).

Lenc, T., Keller, P. E., Varlet, M. & Nozaradan, S. Neural and behavioral evidence for frequency-selective context effects in rhythm processing in humans. Cereb. Cortex Commun. https://doi.org/10.1093/texcom/tgaa037 (2020).

Jacoby, N. & McDermott, J. H. Integer ratio priors on musical rhythm revealed cross-culturally by iterated reproduction. Curr. Biol. 27 , 359–370 (2017).

Hannon, E. E. & Trehub, S. E. Metrical categories in infancy and adulthood. Psychol. Sci. 16 , 48–55 (2005).

Hannon, E. E. & Trehub, S. E. Tuning in to musical rhythms: infants learn more readily than adults. Proc. Natl Acad. Sci. USA 102 , 12639–12643 (2005).

Vuust, P. et al. To musicians, the message is in the meter pre-attentive neuronal responses to incongruent rhythm are left-lateralized in musicians. Neuroimage 24 , 560–564 (2005).

Grahn, J. A. & Brett, M. Rhythm and beat perception in motor areas of the brain. J. Cogn. Neurosci. 19 , 893–906 (2007). This fMRI study investigates participants listening to rhythms of varied complexity .

Toiviainen, P., Burunat, I., Brattico, E., Vuust, P. & Alluri, V. The chronnectome of musical beat. Neuroimage 216 , 116191 (2019).

Chen, J. L., Penhune, V. B. & Zatorre, R. J. Moving on time: brain network for auditory-motor synchronization is modulated by rhythm complexity and musical training. J. Cogn. Neurosci. 20 , 226–239 (2008).

Levitin, D. J., Grahn, J. A. & London, J. The psychology of music: rhythm and movement. Annu. Rev. Psychol. 69 , 51–75 (2018).

Winkler, I., Haden, G. P., Ladinig, O., Sziller, I. & Honing, H. Newborn infants detect the beat in music. Proc. Natl Acad. Sci. USA 106 , 2468–2471 (2009).

Phillips-Silver, J. & Trainor, L. J. Feeling the beat: movement influences infant rhythm perception. Science 308 , 1430–1430 (2005).

Cirelli, L. K., Trehub, S. E. & Trainor, L. J. Rhythm and melody as social signals for infants. Ann. N. Y. Acad. Sci. https://doi.org/10.1111/nyas.13580 (2018).

Cirelli, L. K., Einarson, K. M. & Trainor, L. J. Interpersonal synchrony increases prosocial behavior in infants. Dev. Sci. 17 , 1003–1011 (2014).

Repp, B. H. Sensorimotor synchronization: a review of the tapping literature. Psychon. Bull. Rev. 12 , 969–992 (2005).

Repp, B. H. & Su, Y. H. Sensorimotor synchronization: a review of recent research (2006-2012). Psychon. Bull. Rev. 20 , 403–452 (2013). This review, and Repp (2005), succinctly covers the field of sensorimotor synchronization .

Zarco, W., Merchant, H., Prado, L. & Mendez, J. C. Subsecond timing in primates: comparison of interval production between human subjects and rhesus monkeys. J. Neurophysiol. 102 , 3191–3202 (2009).

Honing, H., Bouwer, F. L., Prado, L. & Merchant, H. Rhesus monkeys ( Macaca mulatta ) sense isochrony in rhythm, but not the beat: additional support for the gradual audiomotor evolution hypothesis. Front. Neurosci. 12 , 475 (2018).

Hattori, Y. & Tomonaga, M. Rhythmic swaying induced by sound in chimpanzees (Pan troglodytes). Proc. Natl Acad. Sci. USA 117 , 936–942 (2020).

Danielsen, A. Presence and Pleasure. The Funk Grooves of James Brown and Parliament (Wesleyan Univ. Press, 2006).

Madison, G., Gouyon, F., Ullen, F. & Hornstrom, K. Modeling the tendency for music to induce movement in humans: first correlations with low-level audio descriptors across music genres. J. Exp. Psychol. Hum. Percept. Perform. 37 , 1578–1594 (2011).

Stupacher, J., Hove, M. J., Novembre, G., Schutz-Bosbach, S. & Keller, P. E. Musical groove modulates motor cortex excitability: a TMS investigation. Brain Cogn. 82 , 127–136 (2013).

Janata, P., Tomic, S. T. & Haberman, J. M. Sensorimotor coupling in music and the psychology of the groove. J. Exp. Psychol. 141 , 54 (2012). Using a systematic approach, this multiple-studies article shows that the concept of groove can be widely understood as a pleasurable drive towards action .

Witek, M. A. et al. A critical cross-cultural study of sensorimotor and groove responses to syncopation among Ghanaian and American university students and staff. Music. Percept. 37 , 278–297 (2020).

Friston, K., Mattout, J. & Kilner, J. Action understanding and active inference. Biol. Cybern. 104 , 137–160 (2011).

Longuet-Higgins, H. C. & Lee, C. S. The rhythmic interpretation of monophonic music. Music. Percept. 1 , 18 (1984).

Sioros, G., Miron, M., Davies, M., Gouyon, F. & Madison, G. Syncopation creates the sensation of groove in synthesized music examples. Front. Psychol. 5 , 1036 (2014).

Witek, M. A., Clarke, E. F., Wallentin, M., Kringelbach, M. L. & Vuust, P. Syncopation, body-movement and pleasure in groove music. PLoS ONE 9 , e94446 (2014).

Kowalewski, D. A., Kratzer, T. M. & Friedman, R. S. Social music: investigating the link between personal liking and perceived groove. Music. Percept. 37 , 339–346 (2020).

Bowling, D. L., Ancochea, P. G., Hove, M. J. & Tecumseh Fitch, W. Pupillometry of groove: evidence for noradrenergic arousal in the link between music and movement. Front. Neurosci. 13 , 1039 (2019).

Matthews, T. E., Witek, M. A. G., Heggli, O. A., Penhune, V. B. & Vuust, P. The sensation of groove is affected by the interaction of rhythmic and harmonic complexity. PLoS ONE 14 , e0204539 (2019).

Matthews, T. E., Witek, M. A., Lund, T., Vuust, P. & Penhune, V. B. The sensation of groove engages motor and reward networks. Neuroimage 214 , 116768 (2020). This fMRI study shows that the sensation of groove engages both motor and reward networks in the brain .

Vaquero, L., Ramos-Escobar, N., François, C., Penhune, V. & Rodríguez-Fornells, A. White-matter structural connectivity predicts short-term melody and rhythm learning in non-musicians. Neuroimage 181 , 252–262 (2018).

Zatorre, R. J., Halpern, A. R., Perry, D. W., Meyer, E. & Evans, A. C. Hearing in the mind’s ear: a PET investigation of musical imagery and perception. J. Cogn. Neurosci. 8 , 29–46 (1996).

Benadon, F. Meter isn’t everything: the case of a timeline-oriented Cuban polyrhythm. N. Ideas Psychol. 56 , 100735 (2020).

London, J., Polak, R. & Jacoby, N. Rhythm histograms and musical meter: a corpus study of Malian percussion music. Psychon. Bull. Rev. 24 , 474–480 (2017).

Huron, D. Is music an evolutionary adaptation? Ann. N. Y. Acad. Sci. 930 , 43–61 (2001).

Koelsch, S. Towards a neural basis of music-evoked emotions. Trends Cogn. Sci. 14 , 131–137 (2010).

Eerola, T. & Vuoskoski, J. K. A comparison of the discrete and dimensional models of emotion in music. Psychol. Music. 39 , 18–49 (2010).

Lonsdale, A. J. & North, A. C. Why do we listen to music? A uses and gratifications analysis. Br. J. Psychol. 102 , 108–134 (2011).

Juslin, P. N. & Laukka, P. Expression, perception, and induction of musical emotions: a review and a questionnaire study of everyday listening. J. N. Music. Res. 33 , 217–238 (2004).

Huron, D. Why is sad music pleasurable? A possible role for prolactin. Music. Sci. 15 , 146–158 (2011).

Brattico, E. et al. It’s sad but I like it: the neural dissociation between musical emotions and liking in experts and laypersons. Front. Hum. Neurosci. 9 , 676 (2015).

PubMed   Google Scholar  

Sachs, M. E., Damasio, A. & Habibi, A. Unique personality profiles predict when and why sad music is enjoyed. Psychol. Music https://doi.org/10.1177/0305735620932660 (2020).

Sachs, M. E., Habibi, A., Damasio, A. & Kaplan, J. T. Dynamic intersubject neural synchronization reflects affective responses to sad music. Neuroimage 218 , 116512 (2020).

Juslin, P. N. & Vastfjall, D. Emotional responses to music: the need to consider underlying mechanisms. Behav. Brain Sci. 31 , 559–575 (2008). Using a novel theoretical framework, the authors propose that the mechanisms that evoke emotions from music are not unique to music .

Rickard, N. S. Intense emotional responses to music: a test of the physiological arousal hypothesis. Psychol. Music. 32 , 371–388 (2004).

Cowen, A. S., Fang, X., Sauter, D. & Keltner, D. What music makes us feel: at least 13 dimensions organize subjective experiences associated with music across different cultures. Proc. Natl Acad. Sci. USA 117 , 1924–1934 (2020).

Argstatter, H. Perception of basic emotions in music: culture-specific or multicultural? Psychol. Music. 44 , 674–690 (2016).

Stevens, C. J. Music perception and cognition: a review of recent cross-cultural research. Top. Cogn. Sci. 4 , 653–667 (2012).

Pearce, M. Cultural distance: a computational approach to exploring cultural influences on music cognition. in Oxford Handbook of Music and the Brain Vol. 31 (Oxford Univ. Press, 2018).

van der Weij, B., Pearce, M. T. & Honing, H. A probabilistic model of meter perception: simulating enculturation. Front. Psychol. 8 , 824 (2017).

Kringelbach, M. L. & Berridge, K. C. Towards a functional neuroanatomy of pleasure and happiness. Trends Cogn. Sci. 13 , 479–487 (2009).

Blood, A. J. & Zatorre, R. J. Intensely pleasurable responses to music correlate with activity in brain regions implicated in reward and emotion. Proc. Natl Acad. Sci. USA 98 , 11818–11823 (2001). This seminal positron emission tomography study shows that the experience of musical chills correlates with activity in the reward system .

Salimpoor, V. N. & Zatorre, R. J. Complex cognitive functions underlie aesthetic emotions: comment on “From everyday emotions to aesthetic emotions: towards a unified theory of musical emotions” by Patrik N. Juslin. Phys. Life Rev. 10 , 279–280 (2013).

Salimpoor, V. N. et al. Interactions between the nucleus accumbens and auditory cortices predict music reward value. Science 340 , 216–219 (2013).

Salimpoor, V. N., Benovoy, M., Larcher, K., Dagher, A. & Zatorre, R. J. Anatomically distinct dopamine release during anticipation and experience of peak emotion to music. Nat. Neurosci. 14 , 257–262 (2011).

Salimpoor, V. N., Benovoy, M., Longo, G., Cooperstock, J. R. & Zatorre, R. J. The rewarding aspects of music listening are related to degree of emotional arousal. PLoS ONE 4 , e7487 (2009).

Mas-Herrero, E., Zatorre, R. J., Rodriguez-Fornells, A. & Marco-Pallares, J. Dissociation between musical and monetary reward responses in specific musical anhedonia. Curr. Biol. 24 , 699–704 (2014).

Martinez-Molina, N., Mas-Herrero, E., Rodriguez-Fornells, A., Zatorre, R. J. & Marco-Pallares, J. Neural correlates of specific musical anhedonia. Proc. Natl Acad. Sci. USA 113 , E7337–E7345 (2016).

Gebauer, L. K., M., L. & Vuust, P. Musical pleasure cycles: the role of anticipation and dopamine. Psychomusicology 22 , 16 (2012).

Shany, O. et al. Surprise-related activation in the nucleus accumbens interacts with music-induced pleasantness. Soc. Cogn. Affect. Neurosci. 14 , 459–470 (2019).

Gold, B. P., Pearce, M. T., Mas-Herrero, E., Dagher, A. & Zatorre, R. J. Predictability and uncertainty in the pleasure of music: a reward for learning? J. Neurosci. 39 , 9397–9409 (2019).

Swaminathan, S. & Schellenberg, E. G. Current emotion research in music psychology. Emot. Rev. 7 , 189–197 (2015).

Madison, G. & Schiölde, G. Repeated listening increases the liking for music regardless of its complexity: implications for the appreciation and aesthetics of music. Front. Neurosci. 11 , 147 (2017).

Corrigall, K. A. & Schellenberg, E. G. Liking music: genres, contextual factors, and individual differences. in Art, Aesthetics, and the Brain (Oxford Univ. Press, 2015).

Zentner, A. Measuring the effect of file sharing on music purchases. J. Law Econ. 49 , 63–90 (2006).

Rentfrow, P. J. & Gosling, S. D. The do re mi’s of everyday life: the structure and personality correlates of music preferences. J. Pers. Soc. Psychol. 84 , 1236–1256 (2003).

Vuust, P. et al. Personality influences career choice: sensation seeking in professional musicians. Music. Educ. Res. 12 , 219–230 (2010).

Rohrmeier, M. & Rebuschat, P. Implicit learning and acquisition of music. Top. Cogn. Sci. 4 , 525–553 (2012).

Münthe, T. F., Altenmüller, E. & Jäncke, L. The musician’s brain as a model of neuroplasticity. Nat. Rev. Neurosci. 3 , 1–6 (2002). This review highlights how professional musicians represent an ideal model for investigating neuroplasticity .

Habibi, A. et al. Childhood music training induces change in micro and macroscopic brain structure: results from a longitudinal study. Cereb. Cortex 28 , 4336–4347 (2018).

Schlaug, G., Jancke, L., Huang, Y., Staiger, J. F. & Steinmetz, H. Increased corpus callosum size in musicians. Neuropsychologia 33 , 1047–1055 (1995).

Baer, L. H. et al. Regional cerebellar volumes are related to early musical training and finger tapping performance. Neuroimage 109 , 130–139 (2015).

Kleber, B. et al. Voxel-based morphometry in opera singers: increased gray-matter volume in right somatosensory and auditory cortices. Neuroimage 133 , 477–483 (2016).

Gaser, C. & Schlaug, G. Brain structures differ between musicians and non-musicians. J. Neurosci. 23 , 9240–9245 (2003). Using a morphometric technique, this study shows a grey matter volume difference in multiple brain regions between professional musicians and a matched control group of amateur musicians and non-musicians .

Sluming, V. et al. Voxel-based morphometry reveals increased gray matter density in Broca’s area in male symphony orchestra musicians. Neuroimage 17 , 1613–1622 (2002).

Palomar-García, M.-Á., Zatorre, R. J., Ventura-Campos, N., Bueichekú, E. & Ávila, C. Modulation of functional connectivity in auditory–motor networks in musicians compared with nonmusicians. Cereb. Cortex 27 , 2768–2778 (2017).

Schneider, P. et al. Morphology of Heschl’s gyrus reflects enhanced activation in the auditory cortex of musicians. Nat. Neurosci. 5 , 688–694 (2002).

Bengtsson, S. L. et al. Extensive piano practicing has regionally specific effects on white matter development. Nat. Neurosci. 8 , 1148–1150 (2005).

Zamorano, A. M., Cifre, I., Montoya, P., Riquelme, I. & Kleber, B. Insula-based networks in professional musicians: evidence for increased functional connectivity during resting state fMRI. Hum. Brain Mapp. 38 , 4834–4849 (2017).

Kraus, N. & Chandrasekaran, B. Music training for the development of auditory skills. Nat. Rev. Neurosci. 11 , 599–605 (2010).

Koelsch, S., Schröger, E. & Tervaniemi, M. Superior pre-attentive auditory processing in musicians. Neuroreport 10 , 1309–1313 (1999).

Münte, T. F., Kohlmetz, C., Nager, W. & Altenmüller, E. Superior auditory spatial tuning in conductors. Nature 409 , 580 (2001).

Seppänen, M., Brattico, E. & Tervaniemi, M. Practice strategies of musicians modulate neural processing and the learning of sound-patterns. Neurobiol. Learn. Mem. 87 , 236–247 (2007).

Guillot, A. et al. Functional neuroanatomical networks associated with expertise in motor imagery. Neuroimage 41 , 1471–1483 (2008).

Bianco, R., Novembre, G., Keller, P. E., Villringer, A. & Sammler, D. Musical genre-dependent behavioural and EEG signatures of action planning. a comparison between classical and jazz pianists. Neuroimage 169 , 383–394 (2018).

Vuust, P., Brattico, E., Seppänen, M., Näätänen, R. & Tervaniemi, M. Practiced musical style shapes auditory skills. Ann. N. Y. Acad. Sci. 1252 , 139–146 (2012).

Bangert, M. & Altenmüller, E. O. Mapping perception to action in piano practice: a longitudinal DC-EEG study. BMC Neurosci. 4 , 26 (2003).

Li, Q. et al. Musical training induces functional and structural auditory-motor network plasticity in young adults. Hum. Brain Mapp. 39 , 2098–2110 (2018).

Herholz, S. C., Coffey, E. B. J., Pantev, C. & Zatorre, R. J. Dissociation of neural networks for predisposition and for training-related plasticity in auditory-motor learning. Cereb. Cortex 26 , 3125–3134 (2016).

Putkinen, V., Tervaniemi, M. & Huotilainen, M. Musical playschool activities are linked to faster auditory development during preschool-age: a longitudinal ERP study. Sci. Rep. 9 , 11310–11310 (2019).

Putkinen, V., Tervaniemi, M., Saarikivi, K., Ojala, P. & Huotilainen, M. Enhanced development of auditory change detection in musically trained school-aged children: a longitudinal event-related potential study. Dev. Sci. 17 , 282–297 (2014).

Jentschke, S. & Koelsch, S. Musical training modulates the development of syntax processing in children. Neuroimage 47 , 735–744 (2009).

Chobert, J., François, C., Velay, J. L. & Besson, M. Twelve months of active musical training in 8-to 10-year-old children enhances the preattentive processing of syllabic duration and voice onset time. Cereb. Cortex 24 , 956–967 (2014).

Moreno, S. et al. Musical training influences linguistic abilities in 8-year-old children: more evidence for brain plasticity. Cereb. Cortex 19 , 712–723 (2009).

Putkinen, V., Huotilainen, M. & Tervaniemi, M. Neural encoding of pitch direction is enhanced in musically trained children and is related to reading skills. Front. Psychol. 10 , 1475 (2019).

Wong, P. C., Skoe, E., Russo, N. M., Dees, T. & Kraus, N. Musical experience shapes human brainstem encoding of linguistic pitch patterns. Nat. Neurosci. 10 , 420–422 (2007).

Virtala, P. & Partanen, E. Can very early music interventions promote at-risk infants’ development? Ann. N. Y. Acad. Sci. 1423 , 92–101 (2018).

Flaugnacco, E. et al. Music training increases phonological awareness and reading skills in developmental dyslexia: a randomized control trial. PLoS ONE 10 , e0138715 (2015).

Fiveash, A. et al. A stimulus-brain coupling analysis of regular and irregular rhythms in adults with dyslexia and controls. Brain Cogn. 140 , 105531 (2020).

Schellenberg, E. G. Correlation = causation? music training, psychology, and neuroscience. Psychol. Aesthet. Creat. Arts 14 , 475–480 (2019).

Sala, G. & Gobet, F. Cognitive and academic benefits of music training with children: a multilevel meta-analysis. Mem. Cogn. 48 , 1429–1441 (2020).

Saffran, J. R. Musical learning and language development. Ann. N. Y. Acad. Sci. 999 , 397–401 (2003).

Friston, K. The free-energy principle: a rough guide to the brain? Trends Cogn. Sci. 13 , 293–301 (2009).

Pearce, M. T. Statistical learning and probabilistic prediction in music cognition: mechanisms of stylistic enculturation. Ann. N. Y. Acad. Sci. 1423 , 378–395 (2018).

Article   PubMed Central   Google Scholar  

Novembre, G., Knoblich, G., Dunne, L. & Keller, P. E. Interpersonal synchrony enhanced through 20 Hz phase-coupled dual brain stimulation. Soc. Cogn. Affect. Neurosci. 12 , 662–670 (2017).

Konvalinka, I. et al. Frontal alpha oscillations distinguish leaders from followers: multivariate decoding of mutually interacting brains. Neuroimage 94C , 79–88 (2014).

Novembre, G., Mitsopoulos, Z. & Keller, P. E. Empathic perspective taking promotes interpersonal coordination through music. Sci. Rep. 9 , 12255 (2019).

Wolpert, D. M., Ghahramani, Z. & Jordan, M. I. An internal model for sensorimotor integration. Science 269 , 1880–1882 (1995).

Patel, A. D. & Iversen, J. R. The evolutionary neuroscience of musical beat perception: the action simulation for auditory prediction (ASAP) hypothesis. Front. Syst. Neurosci. 8 , 57 (2014).

Sebanz, N. & Knoblich, G. Prediction in joint action: what, when, and where. Top. Cogn. Sci. 1 , 353–367 (2009).

Friston, K. J. & Frith, C. D. Active inference, communication and hermeneutics. Cortex 68 , 129–143 (2015). This article proposes a link between active inference, communication and hermeneutics .

Konvalinka, I., Vuust, P., Roepstorff, A. & Frith, C. D. Follow you, follow me: continuous mutual prediction and adaptation in joint tapping. Q. J. Exp. Psychol. 63 , 2220–2230 (2010).

Wing, A. M. & Kristofferson, A. B. Response delays and the timing of discrete motor responses. Percept. Psychophys. 14 , 5–12 (1973).

Repp, B. H. & Keller, P. E. Sensorimotor synchronization with adaptively timed sequences. Hum. Mov. Sci. 27 , 423–456 (2008).

Vorberg, D. & Schulze, H.-H. Linear phase-correction in synchronization: predictions, parameter estimation, and simulations. J. Math. Psychol. 46 , 56–87 (2002).

Novembre, G., Sammler, D. & Keller, P. E. Neural alpha oscillations index the balance between self-other integration and segregation in real-time joint action. Neuropsychologia 89 , 414–425 (2016). Using dual-EEG, the authors propose alpha oscillations as a candidate for regulating the balance between internal and external information in joint action .

Keller, P. E., Knoblich, G. & Repp, B. H. Pianists duet better when they play with themselves: on the possible role of action simulation in synchronization. Conscious. Cogn. 16 , 102–111 (2007).

Fairhurst, M. T., Janata, P. & Keller, P. E. Leading the follower: an fMRI investigation of dynamic cooperativity and leader-follower strategies in synchronization with an adaptive virtual partner. Neuroimage 84 , 688–697 (2014).

Heggli, O. A., Konvalinka, I., Kringelbach, M. L. & Vuust, P. Musical interaction is influenced by underlying predictive models and musical expertise. Sci. Rep. 9 , 1–13 (2019).

Heggli, O. A., Cabral, J., Konvalinka, I., Vuust, P. & Kringelbach, M. L. A Kuramoto model of self-other integration across interpersonal synchronization strategies. PLoS Comput. Biol. 15 , e1007422 (2019).

Heggli, O. A. et al. Transient brain networks underlying interpersonal strategies during synchronized action. Soc. Cogn. Affect. Neurosci. 16 , 19–30 (2020). This EEG study shows that differences in interpersonal synchronization are reflected by activity in a temporoparietal network .

Patel, A. D. Music, Language, and the Brain (Oxford Univ. Press, 2006).

Molnar-Szakacs, I. & Overy, K. Music and mirror neurons: from motion to ‘e’motion. Soc. Cogn. Affect. Neurosci. 1 , 235–241 (2006).

Beaty, R. E., Benedek, M., Silvia, P. J. & Schacter, D. L. Creative cognition and brain network dynamics. Trends Cogn. Sci. 20 , 87–95 (2016).

Limb, C. J. & Braun, A. R. Neural substrates of spontaneous musical performance: an FMRI study of jazz improvisation. PLoS ONE 3 , e1679 (2008).

Liu, S. et al. Neural correlates of lyrical improvisation: an FMRI study of freestyle rap. Sci. Rep. 2 , 834 (2012).

Rosen, D. S. et al. Dual-process contributions to creativity in jazz improvisations: an SPM-EEG study. Neuroimage 213 , 116632 (2020).

Boasen, J., Takeshita, Y., Kuriki, S. & Yokosawa, K. Spectral-spatial differentiation of brain activity during mental imagery of improvisational music performance using MEG. Front. Hum. Neurosci. 12 , 156 (2018).

Berkowitz, A. L. & Ansari, D. Generation of novel motor sequences: the neural correlates of musical improvisation. Neuroimage 41 , 535–543 (2008).

Loui, P. Rapid and flexible creativity in musical improvisation: review and a model. Ann. N. Y. Acad. Sci. 1423 , 138–145 (2018).

Beaty, R. E. The neuroscience of musical improvisation. Neurosci. Biobehav. Rev. 51 , 108–117 (2015).

Vuust, P. & Kringelbach, M. L. Music improvisation: a challenge for empirical research. in Routledge Companion to Music Cognition (Routledge, 2017).

Norgaard, M. Descriptions of improvisational thinking by artist-level jazz musicians. J. Res. Music. Educ. 59 , 109–127 (2011).

Kringelbach, M. L. & Deco, G. Brain states and transitions: insights from computational neuroscience. Cell Rep. 32 , 108128 (2020).

Deco, G. & Kringelbach, M. L. Hierarchy of information processing in the brain: a novel ‘intrinsic ignition’ framework. Neuron 94 , 961–968 (2017).

Pinho, A. L., de Manzano, O., Fransson, P., Eriksson, H. & Ullen, F. Connecting to create: expertise in musical improvisation is associated with increased functional connectivity between premotor and prefrontal areas. J. Neurosci. 34 , 6156–6163 (2014).

Pinho, A. L., Ullen, F., Castelo-Branco, M., Fransson, P. & de Manzano, O. Addressing a paradox: dual strategies for creative performance in introspective and extrospective networks. Cereb. Cortex 26 , 3052–3063 (2016).

de Manzano, O. & Ullen, F. Activation and connectivity patterns of the presupplementary and dorsal premotor areas during free improvisation of melodies and rhythms. Neuroimage 63 , 272–280 (2012).

Beaty, R. E. et al. Robust prediction of individual creative ability from brain functional connectivity. Proc. Natl Acad. Sci. USA 115 , 1087–1092 (2018).

Daikoku, T. Entropy, uncertainty, and the depth of implicit knowledge on musical creativity: computational study of improvisation in melody and rhythm. Front. Comput. Neurosci. 12 , 97 (2018).

Belden, A. et al. Improvising at rest: differentiating jazz and classical music training with resting state functional connectivity. Neuroimage 207 , 116384 (2020).

Arkin, C., Przysinda, E., Pfeifer, C. W., Zeng, T. & Loui, P. Gray matter correlates of creativity in musical improvisation. Front. Hum. Neurosci. 13 , 169 (2019).

Bashwiner, D. M., Wertz, C. J., Flores, R. A. & Jung, R. E. Musical creativity “revealed” in brain structure: interplay between motor, default mode, and limbic networks. Sci. Rep. 6 , 20482 (2016).

Przysinda, E., Zeng, T., Maves, K., Arkin, C. & Loui, P. Jazz musicians reveal role of expectancy in human creativity. Brain Cogn. 119 , 45–53 (2017).

Large, E. W., Kim, J. C., Flaig, N. K., Bharucha, J. J. & Krumhansl, C. L. A neurodynamic account of musical tonality. Music. Percept. 33 , 319–331 (2016).

Large, E. W. & Palmer, C. Perceiving temporal regularity in music. Cogn. Sci. 26 , 1–37 (2002). This article proposes an oscillator-based approach for the perception of temporal regularity in music .

Cannon, J. J. & Patel, A. D. How beat perception co-opts motor neurophysiology. Trends Cogn. Sci. 25 , 137–150 (2020). The authors propose that cyclic time-keeping activity in the supplementary motor area, termed ‘proto-actions’, is organized by the dorsal striatum to support hierarchical metrical structures .

Keller, P. E., Novembre, G. & Loehr, J. Musical ensemble performance: representing self, other and joint action outcomes. in Shared Representations: Sensorimotor Foundations of Social Life Cambridge Social Neuroscience (eds Cross, E. S. & Obhi, S. S.) 280-310 (Cambridge Univ. Press, 2016).

Rao, R. P. & Ballard, D. H. Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects. Nat. Neurosci. 2 , 79–87 (1999).

Clark, A. Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behav. Brain Sci. 36 , 181–204 (2013).

Kahl, R. Selected Writings of Hermann Helmholtz (Wesleyan Univ. Press, 1878).

Gregory, R. L. Perceptions as hypotheses. Philos. Trans. R. Soc. Lond. B Biol. Sci. 290 , 181–197 (1980).

Gibson, J. J. The Ecological Approach to Visual Perception (Houghton Mifflin, 1979).

Fuster, J. The Prefrontal Cortex Anatomy, Physiology and Neuropsychology of the Frontal Lobe (Lippincott-Raven, 1997).

Neisser, U. Cognition and Reality: Principles and Implications of Cognitive Psychology (W H Freeman/Times Books/ Henry Holt & Co, 1976).

Arbib, M. A. & Hesse, M. B. The Construction of Reality (Cambridge Univ. Press, 1986).

Cisek, P. & Kalaska, J. F. Neural mechanisms for interacting with a world full of action choices. Annu. Rev. Neurosci. 33 , 269–298 (2010).

Isomura, T., Parr, T. & Friston, K. Bayesian filtering with multiple internal models: toward a theory of social intelligence. Neural Comput. 31 , 2390–2431 (2019).

Friston, K. & Frith, C. A duet for one. Conscious. Cogn. 36 , 390–405 (2015).

Hunt, B. R., Ott, E. & Yorke, J. A. Differentiable generalized synchronization of chaos. Phys. Rev. E 55 , 4029–4034 (1997).

Ghazanfar, A. A. & Takahashi, D. Y. The evolution of speech: vision, rhythm, cooperation. Trends Cogn. Sci. 18 , 543–553 (2014).

Wilson, M. & Wilson, T. P. An oscillator model of the timing of turn-taking. Psychon. Bull. Rev. 12 , 957–968 (2005).

Download references

Acknowledgements

Funding was provided by The Danish National Research Foundation (DNRF117). The authors thank E. Altenmüller and D. Huron for comments on early versions of the manuscript.

Author information

Authors and affiliations.

Center for Music in the Brain, Aarhus University and The Royal Academy of Music (Det Jyske Musikkonservatorium), Aarhus, Denmark

Peter Vuust, Ole A. Heggli & Morten L. Kringelbach

Wellcome Centre for Human Neuroimaging, University College London, London, UK

Karl J. Friston

Department of Psychiatry, University of Oxford, Oxford, UK

Morten L. Kringelbach

Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK

You can also search for this author in PubMed   Google Scholar

Contributions

The authors contributed equally to all aspects of this article.

Corresponding author

Correspondence to Peter Vuust .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Peer review

Peer review information.

Nature Reviews Neuroscience thanks D. Sammler and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Patterns of pitched sounds unfolding over time, in accordance with cultural conventions and constraints.

The combination of multiple, simultaneously pitched sounds to form a chord, and subsequent chord progressions, a fundamental building block of Western music. The rules of harmony are the hierarchically organized expectations for chord progressions.

The structured arrangement of successive sound events over time, a primary parameter of musical structure. Rhythm perception is based on the perception of duration and grouping of these events and can be achieved even if sounds are not discrete, such as amplitude-modulated sounds.

Mathematically, the expected values or means of random variables.

The ability to extract statistical regularities from the world to learn about the environment.

In Western music, the organization of melody and harmony in a hierarchy of relations, often pointing towards a referential pitch (the tonal centre or the tonic).

A predictive framework governing the interpretation of regularly recurring patterns and accents in rhythm.

The output of a model generating outcomes from their causes. In predictive coding, the prediction is generated from expected states of the world and compared with observed outcomes to form a prediction error.

The subjective experience accompanying a strong expectation that a particular event will occur.

An enactive generalization of predictive coding that casts both action and perception as minimizing surprise or prediction error (active inference is considered a corollary of the free-energy principle).

A quantity used in predictive coding to denote the difference between an observation or point estimate and its predicted value. Predictive coding uses precision-weighted prediction errors to update expectations that generate predictions.

Expectations of musical events based on prior knowledge of regularities and patterns in musical sequences, such as melodies and chords.

Expectations of specific events or patterns in a familiar musical sequence.

Short-lived expectations that dynamically shift owing to the ongoing musical context, such as when a repeated musical phrase causes the listener to expect similar phrases as the work continues.

The inverse variance or negative entropy of a random variable. It corresponds to a second-order statistic (for example, a second-order moment) of the variable’s probability distribution or density. This can be contrasted with the mean or expectation, which constitutes a first-order statistic (for example, a first-order moment).

(MMN). A component of the auditory event-related potential recorded with electroencephalography or magnetoencephalography related to a change in different sound features such as pitch, timbre, location of the sound source, intensity and rhythm. It peaks approximately 110–250 ms after change onset and is typically recorded while participants’ attention is distracted from the stimulus, usually by watching a silent film or reading a book. The amplitude and latency of the MMN depends on the deviation magnitude, such that larger deviations in the same context yield larger and faster MMN responses.

(fMRI). A neuroimaging technique that images rapid changes in blood oxygenation levels in the brain.

In the realm of contemporary music, a persistently repeated pattern played by the rhythm section (usually drums, percussion, bass, guitar and/or piano). In music psychology, the pleasurable sensation of wanting to move.

The perceptual correlate of periodicity in sounds that allows their ordering on a frequency-related musical scale.

Also known as tone colour or tone quality, the perceived sound quality of a sound, including its spectral composition and its additional noise characteristics.

The pitch class containing all pitches separated by an integer number of octaves. Humans perceive a similarity between notes having the same chroma.

The contextual unexpectedness or surprise associated with an event.

In the Shannon sense, the expected surprise or information content (self-information). In other words, it is the uncertainty or unpredictability of a random variable (for example, an event in the future).

(MEG). A neuroimaging technique that measures the magnetic fields produced by naturally occurring electrical activity in the brain.

A very small electrical voltage generated in the brain structures in response to specific events or stimuli.

Psychologically, consonance is when two or more notes sound together with an absence of perceived roughness. Dissonance is the antonym of consonance. Western listeners consider intervals produced by frequency ratios such as 1:2 (octave), 3:2 (fifth) or 4:3 (fourth) as consonant. Dissonances are intervals produced by frequency ratios formed from numbers greater than 4.

Stereotypical patterns consisting of two or more chords that conclude a phrase, section or piece of music. They are often used to establish a sense of tonality.

(EEG). An electrophysiological method that measures electrical activity of the brain.

A method of analysing steady-state evoked potentials arising from stimulation or aspects of stimulation repeated at a fixed rate. An example of frequency tagging analysis is shown in Fig.  1c .

A shift of rhythmic emphasis from metrically strong accents to weak accents, a characteristic of multiple musical genres, such as funk, jazz and hip hop.

In Aristotelian ethics, refers to a life well lived or human flourishing, and in affective neuroscience, it is often used to describe meaningful pleasure.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Cite this article.

Vuust, P., Heggli, O.A., Friston, K.J. et al. Music in the brain. Nat Rev Neurosci 23 , 287–305 (2022). https://doi.org/10.1038/s41583-022-00578-5

Download citation

Accepted : 22 February 2022

Published : 29 March 2022

Issue Date : May 2022

DOI : https://doi.org/10.1038/s41583-022-00578-5

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

This article is cited by

Improved emotion differentiation under reduced acoustic variability of speech in autism.

• Mathilde Marie Duville
• Luz María Alonso-Valerdi
• David I. Ibarra-Zarate

BMC Medicine (2024)

Exploring the neural underpinnings of chord prediction uncertainty: an electroencephalography (EEG) study

• Kentaro Ono
• Ryohei Mizuochi
• Shigeto Ymawaki

Scientific Reports (2024)

Effekte von klassischer Musik oder von Heavy Metal bei Mensch und Tier: Implikationen für die Intensivmedizin

• Hans-Joachim Trappe
• Eva-Maria Völkel
• Gerald Reiner

Medizinische Klinik - Intensivmedizin und Notfallmedizin (2024)

Frontal and cerebellar contributions to pitch and rhythm processing: a TMS study

• Silvia Picazio
• Barbara Magnani
• Laura Petrosini

Brain Structure and Function (2024)

Care intervention on psychological outcomes among patients admitted to intensive care unit: an umbrella review of systematic reviews and meta-analyses

• Yafang Zheng
• Lijuan Zhang
• Jingxia Zheng

Systematic Reviews (2023)

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Music Research Guide: Research tools

• Research tools
• Full A-Z list of music databases
• Mobile apps
• Music at MIT
• Free web resources

In this guide

Locate music books, recordings, scores, articles, & e-resources.

• Find music journal articles (MIT access)
• Streaming audio and video (MIT access)

Reference works

• "Search Our Collections" (MIT Libraries catalog) To find specific materials owned by MIT.
• Search Our Collections Searches MIT collections and most MIT-licensed e-resources, including full-text articles.
• Finding music materials in MIT "Search Our Collections" Search tips for finding music materials in Search Our Collections.
• Music call numbers

Find music journal articles

These sources may list articles not listed in Search our Collections:

• Music Index Online (journal articles) Indexes music articles in journals 1970-present.
• RILM Abstracts of Music Literature with Full Text (journal articles and more) RILM Abstracts of Music Literature with Full Text expands and enhances the unrivaled global bibliography of writings on music with content from 260 key periodicals published from the early 20th century to the present. It offers articles and reviews as well as obituaries, editorials, correspondence, advertisements, and news in full text, which can be searched and browsed for each issue, cover to cover. Each year new journals are being added to the full-text collection.
• JSTOR Scholarly Journal Archive (full-text journal articles)
• Oxford Music Online (includes Grove's Dictionary of Music) Encyclopedia of Popular Music, Grove Music Online, Oxford Dictionary of Music, and Oxford Companion to Music.

Streaming audio and video

Streaming audio:

• Naxos Music Library Over two million tracks of music.
• Naxos mobile app Create and download playlists of your favorite pieces from the Naxos Music Library.
• Naxos Jazz Roughly 200 tracks representing a variety of jazz styles and periods.
• Music and Performing Arts Over 5 million tracks from Alexander Street Press: includes American Song, Classical Music Library, Contemporary World Music, Jazz Music Library, and Smithsonian Global Sound
• DRAM [Database of Recorded American Music] American music from folk to opera, Native American to jazz, 19th century classical to early rock, musical theater, contemporary, electronic and beyond.

Streaming video:

• Naxos Video Library Classical music performances, opera, ballet, live concerts, documentaries, and more.
• Medici.TV Classical music including concerts, operas, ballets, documentaries, master classes, artist profiles, and educational films.
• Met Opera on Demand From the Metropolitan Opera in New York.
• Digital Concert Hall From the Berlin Philharmonic: live broadcasts, videos, and a large archive of recordings. Create a user account for access.
• Opera in Video From Alexander Street Press.
• Classical Music Library More from Alexander Street Press. Use the Menu feature to access other collections, including world music, jazz, and more.

General reference works

• Oxford Reference Online Concise definitions and in-depth encyclopedic entries on a wide range of subjects within the broad field of music.
• Baker's Biographical Dictionary of Musicians
• Oxford Bibliographies Online: Music (MIT access) Annotated bibliographies and research guides by music scholars.
• World music
• Garland Encyclopedia of World Music Online

Specific topics

• Music Industry Data (MIT access) Statistical chart data across all music genres. Formerly Academic Charts Online (ACO).
• RISM (International Inventory of Musical Sources) Music manuscripts before 1800.
• HathiTrust Digital Library Online e-books & more from major research partner institutions.
• Oxford Reference Online (MIT access)
• Early English Books Online [EEBO], includes scores (MIT access)
• Eighteenth Century Collections Online [ECCO], includes scores (MIT access)
• Internet Archive (texts)

Lewis Music Library Department Head

More ways to get help

Ask Us Ask a question, make an appointment, give feedback, or visit us.

Other library services

• Suggest a purchase (MIT only)
• Interlibrary borrowing (MIT only)

Related guides

Research guide: Music

Research guide: Theater Arts Music quick guides:

• Electronic music
• Equipment available in the Lewis Music Library
• Music of the United States
• Musical theater
• Pop and rock music
• Social justice and music
• Next: Full A-Z list of music databases >>
• Last Updated: May 8, 2023 4:39 PM
• URL: https://libguides.mit.edu/music

• Harvard Library
• Research Guides
• Faculty of Arts & Sciences Libraries

Music Research Guide

• HOLLIS (Library catalog and more)
• Dictionaries, Encyclopedias, Bibliographies
• Recordings and Videos
• Scores and Sheet Music
• Concert Reviews
• Collected Works Editions
• Dissertations and Theses
• Music in Special Collections
• Ethnomusicology Research @ Harvard
• Jazz Research @ Harvard This link opens in a new window
• American Indigenous Music
• Senior Thesis Style Guide: Footnotes
• Senior Thesis Style Guide: Bibliography
• Multimedia Production Resources

Finding Articles with a Citation

• Harvard Library: Journals Search Find the full text of an article if you already have its title and/or a partial citation.
• Harvard Library Bookmark Need access to an online article? Use this bookmarklet to get quick access to subscriptions purchased by Harvard Library.

Using Article Indexes

Use specialized periodical indexes and bibliographies to find articles, book chapters, reviews, and more. A number of these indexes include the full text of articles; if not, look for the "Try Harvard Library" link to automatically search Harvard's e-resources for the full text.

Key Article Indexes

These indexes are especially useful for research in music and performance:

• RILM Abstracts of Music Literature An international bibliography of music articles, collections, and books. Indexes scholarly articles, reviews, conference papers, essays, book chapters, dissertations and more. Strong in ethnomusicological journals and topics. more... less... RILM Abstracts of Music Literature features a wealth of content from the early 1800s through the present with some content coverage extending back as far as the late 18th century. Updated monthly, the database includes coverage of relevant articles from more than 10,000 journals, many of which are not specifically devoted to music. RILM Abstracts of Music Literature also includes nearly 850,000 records with over 52,000 new records are added every year.
• Music Periodicals Database An index of articles and reviews from over 400 scholarly and popular music periodicals (1874-present), plus full text for around 140 journals. (Formerly known as International Index to Music Periodicals, IIMP) more... less... An electronic index of music publications, IIMP draws its current content from nearly 400 international music periodicals from over 30 countries, and also indexes feature music articles and obituaries appearing in The New York Times and The Washington Post. This service contains publications from Acta Musicologica: Societe Internationale de Musicologie to the Music Educators Journal to Zeitschrift fuer Musikwissenschaft (1918-1935).
• Music Index Online Good for research on popular music, ethnomusicology, and reviews. The online version covers articles published from 1970-present; earlier volumes are available in print: Loeb Music Library ML118.M84 (1949-present) more... less... The Music Index Online provides citations to articles, book and record reviews, first performances, and obituaries from over 690 international music periodicals covering a wide range of historical, musicological, and ethnomusicological topics.
• RIPM: Retrospective Index to Music Periodicals (Full Text) Collection of primary source material for the study of music and musical life from approximately 1800 to 1950.
• European and North American Music Periodicals (Full Text) Part of the RIPM Preservation Series, a supplement to the RIPM Retrospective Index. Titles include one hundred journals dealing with musical life in world capitals and several monumental journals including Musical America.
• RIPM Jazz Periodicals Full-text American jazz magazines and journals from the 20th century.
• JSTOR Full-text access to scholarly articles from over 50 music periodicals published from the 1860s - 2000s. Remember: JSTOR does not include the most recent issues of journals; the following databases offer more current coverage: more... less... Includes all titles in the JSTOR collection, excluding recent issues. JSTOR (www.jstor.org) is a not-for-profit organization with a dual mission to create and maintain a trusted archive of important scholarly journals, and to provide access to these journals as widely as possible. Content in JSTOR spans many disciplines, primarily in the humanities and social sciences. For complete lists of titles and collections, please refer to http://www.jstor.org/about/collection.list.html.
• Performing Arts Periodicals Database An index of articles and reviews from over 300 performing arts journals (1864-present), covering theatre, film, dance, opera, and stagecraft, plus full text from over 100 journals. (Formerly known as International Index to Performing Arts, IIPA) more... less... A multidisciplinary electronic index to the performing arts periodical literature with full text for over 100 journals. The index covers material from 1998 forward, with some retrospective listings.
• ProQuest - Entertainment Industry Magazine Archive A full-text resource for the study of the film and entertainment industries, from the era of vaudeville and silent movies to 2000. The collection includes US and UK trade magazines covering film, music, broadcasting, and theater, film fan magazines, and popular music magazines. Indexing includes not only articles and reviews, but covers and advertisements. more... less... Primary sources for film, broadcasting, popular music and theatre, 1880 – 2000##Our new digital archive is sure to receive rave reviews fromthose wanting to know more about behind-the-scenes activities of the music, film, and entertainment industries. By providing the complete runs of major trade and consumer magazines, from their inception to 2000, it arms students and researchers with the primary source material needed to develop a contextual understanding of the entertainment industry as it evolved over the 20th century.
• Academic Search Premier (Harvard Login) A multi-disciplinary index with the full text of over 8500 journals, both popular and scholarly. Especially useful for interdisciplinary topics. more... less... Academic Search Premier (ASP) is a multi-disciplinary database that includes citations and abstracts from over 4,700 scholarly publications (journals, magazines and newspapers). Full text is available for more than 3,600 of the publications and is searchable.

Popular Music, Popular Press

Try these sites for non-academic newspaper and magazine articles - reviews, interviews, profiles, and more - about popular music.

• Rock’s Backpages Collected reviews, interviews, and articles about popular music from the 1950s to the present. more... less... 10,000 articles, interviews, and reviews from music writers, journalists, and critics, from the late 1950s to the present day from publications such as Billboard, Cashbox, Rolling Stone, Melody Maker, and many smaller local publications (city papers). Searchable by keyword, date, subject, publication, writer, artist or band; content ranges from Justin Timberlake to Johnny Cash to Bob Dylan.
• Rolling Stone Archive Full text of Rolling Stone magazine, from 1967-present.
• ProQuest - Entertainment Industry Magazine Archive A full-text collection for the study of the film and entertainment industries, including trade magazines, fanzines, and popular music magazines. more... less... Primary sources for film, broadcasting, popular music and theatre, 1880 – 2000##Our new digital archive is sure to receive rave reviews fromthose wanting to know more about behind-the-scenes activities of the music, film, and entertainment industries. By providing the complete runs of major trade and consumer magazines, from their inception to 2000, it arms students and researchers with the primary source material needed to develop a contextual understanding of the entertainment industry as it evolved over the 20th century.
• NexisUni Full-text newspaper articles from the last several decades: useful for current news and reviews
• Readers' Guide Retrospective (1890-1982) An index of popular and general interest magazines published in the United States and Canada. more... less... http://nrs.harvard.edu/urn-3:hul.eresource:holliswb
• Periodicals Index Online An index to tables of contents of periodicals in the arts, humanities, and social sciences.

Multidisciplinary Sources

• Anthropology Plus more... less... Anthropology Plus is the world’s most comprehensive, focused index covering publications in anthropology and related disciplines issued from the mid-19th century to the present. Social, cultural, physical, biological, and linguistic anthropology and archaeology (particularly prehistoric archaeology) are indexed comprehensively. Closely related fields such as folklore, material culture, human evolution, primatology, zooarchaeology, museum studies, and visual studies are all well represented.####Anthropology Plus unites two premier indexes produced in two hemispheres – Anthropological Literature (AL) at Harvard University and Anthropological Index Online (AIO) at the British Museum -- both indexing many of the core anthropology publications while individually covering many lesser-known and local publications, yielding in-depth coverage of a broad array of the world’s scholarship in anthropology.

• Arts and Humanities Citation Index (ISI Web of Science) (1975-) more... less... Arts & Humanities Citation Index, published by the Institute for Scientific Information (ISI), is a multidisciplinary database covering the journal literature of the arts and humanities. It indexes 1,100 of the world's leading arts and humanities journals, as well as covering individually selected, relevant items from over 7,000 major science and social science journals. Because the information stored about each article includes the article's cited reference list (often called its bibliography), you can also search the database for articles that cite a known author or work.
• Academic Search Premier (Harvard Login) more... less... Academic Search Premier (ASP) is a multi-disciplinary database that includes citations and abstracts from over 4,700 scholarly publications (journals, magazines and newspapers). Full text is available for more than 3,600 of the publications and is searchable.
• Ethnic NewsWatch more... less... Ethnic NewsWatch is an interdisciplinary, bilingual (English and Spanish), and comprehensive full text database of the newspapers, magazines, and journals of the ethnic, minority and native press.
• NexisUni Full text articles from thousands of new sources (1980s-present) such as wire services, Time, Newsweek, New York Times, Boston Globe, Washington Post (all major newspapers). Good for finding performance or recording reviews.
• << Previous: How to Find...
• Next: Recordings and Videos >>

Except where otherwise noted, this work is subject to a Creative Commons Attribution 4.0 International License , which allows anyone to share and adapt our material as long as proper attribution is given. For details and exceptions, see the Harvard Library Copyright Policy ©2021 Presidents and Fellows of Harvard College.

ORIGINAL RESEARCH article

Impact of background music on reading comprehension: influence of lyrics language and study habits.

• 1 Department of Applied Psychology, College of Sports and Health, Shandong Sport University, Jinan, China
• 2 School of Physical Education, Shandong University, Jinan, China
• 3 Department of Insurance, Shandong University of Finance and Economics, Jinan, China
• 4 School of Psychology, Qufu Normal University, Qufu, China
• 5 Zizhong Middle School, Linqing, China
• 6 College of Physical Education and Health, Guangxi Normal University, Guilin, China

Numerous studies have explored the effects of background music on reading comprehension, however, little is known about how native language (L1) lyrics and second language (L2) lyrics in background music influence reading comprehension performance for college students. The present study used a mixed experimental design to examine the effects of listening habits (between-participants variable: non-listeners or listeners), music type (between-participants variable: L1 (Mandarin) pop music, L2 (English) pop music or no music) and text language (within-participants variable: L1 or L2) on reading comprehension of college students in East China. A total of 90 participants (50 females) were screened into non- listeners ( n  = 45) and listeners ( n  = 45), and then were randomly assigned to one of three groups: Mandarin pop music group ( n = 30), English pop music group ( n  = 30) and no music group ( n  = 30). The results showed that reading comprehension performance was negatively affected by music with lyrics compared to the no music condition. Furthermore, Chinese/English reading comprehension was reduced more by pop music in the same language as the written texts. As expected, non-listeners were more negatively affected by music with lyrics than listeners. For both listeners and non-listeners, average reading comprehension accuracy rates were the lowest in the condition of music with native language lyrics. Overall, our research findings indicate that listening to pop music with lyrics reduces reading comprehension performance. However, listening to background music cause much less distraction if the students commonly listen to music while reading. The current study supports the duplex-mechanism account of auditory distraction.

1 Introduction

Listening to music while studying is a common and popular trend for college students. Calderwood et al. (2014) found that 59% of the college students chose to listen to music during a 3-h study session, with 21% listening for more than 90% of the time. Although several studies have demonstrated positive effects of background instrumental music on reading comprehension ( Carlson et al., 2004 ; Khaghaninejad et al., 2016 ) and second language learning ( Kang and Williamson, 2012 ), irrelevant sound from vocal music may cause auditory distraction from the task at hand ( Martin et al., 1988 ; Furnham and Strbac, 2002 ; Perham and Currie, 2014 ; Zhang et al., 2018 ; Du et al., 2020 ). Efficient learning is extremely important for college students. However, high levels of auditory distraction will not only affect efficient learning, but also impair mental and physical function and cause irritation and headaches in schools ( Astolfi et al., 2019 ). Thus, it is important to explore the mechanisms that produce auditory distraction. According to the duplex-mechanism account of auditory distraction, the disruptive effect can be induced by interference-by-process or attentional capture ( Marsh et al., 2008 , 2009 ). To date, previous studies investigating the impact of music on reading comprehension have primarily focused on differences between instrumental and lyrical music (e.g., Erten et al., 2015 ), as well as the influence of differences in musical volume and speed (e.g., Thompson et al., 2012 ). Notably, these studies have not taken into consideration differences in participant preferences for listening to music while reading. In contrast, the present study investigated how differences in the lyrical language of the same song differentially influence reading comprehension based on reported music-listening habits. With the aim of testing the duplex-mechanism account of auditory distraction, our study explored the interactive effects of native language (L1) lyrics and second language (L2) lyrics in music on reading comprehension performance in L1 and L2 for listeners and non-listeners by using a 3-factor mixed experimental design.

1.1 A duplex-mechanism account of auditory distraction

According to the duplex-mechanism account of auditory distraction, there are two functionally different types of auditory distraction. Interference-by-process occurs when a similar process used consciously to complete a focal task competes with the involuntary processing of sound. On the other hand, regardless of the task processes involved, attentional capture occurs when the sound triggers a disengagement of attention from the dominant task ( Hughes, 2014 ). For example, semantic speech (e.g., “orange, banana, strawberry”) can cause distraction effects on semantic-based cognitive tasks (e.g., free recall of visually presented words “apple, mango, pear”) ( Marsh et al., 2008 ). According to the interference-by-process theory, semantically similar speech automatically spreads activation through a long-term semantic network, interfering with the similar process of navigating such networks to retrieve information for the focal task ( Marsh and Jones, 2010 ; Hughes, 2014 ). Interference-by-process explains the semantic distraction effects. Attentional capture falls into two categories: When a sound’s unique content (such as one’s name or one’s native language) gives it the ability to deflect attention, a specific attentional capture takes place. In contrast, when an occurrence draws attention despite having nothing inherently attention-grabbing about it, but rather because of the context in which it takes place, nonspecific attentional capture is created ( Eimer et al., 1996 ). For example, a sound “B” in “CCCCCBCC” or a sound “C” in “BBBBBCBB.” Our study focused on interference-by-process and a specific attentional capture.

1.2 The impact of background music on reading comprehension

Reading comprehension, an important and necessary skill for effective academic learning in college, refers to the active process by which individuals understand and construct the meaning of texts based on prior knowledge and experience ( Perfetti et al., 2005 ). Kämpfe et al. (2010) claimed that reading might be more disturbed by vocal music than by instrumental music ( Kämpfe et al., 2010 ). The duplex-mechanism account of auditory distraction has been supported by research evidence demonstrating the disruptive effects of background speech on various memory tasks such as serial short-term memory tasks. However, little is known about supporting evidence from the distraction effects of L1/L2 lyrics on L1/L2 reading comprehension among listeners and non-listeners. According to the simple view of reading model, reading comprehension consists of only two parts, word recognition and language comprehension, and both parts are necessary for reading success ( Hoover and Gough, 1990 ). For college students, mature readers whose word recognition has attained to a level of automation, language comprehension plays the more important role in reading comprehension. Lyrics in music contain semantic information, which will interfere with language comprehension ( Martin et al., 1988 ; Oswald et al., 2000 ). Thus, we expect that lyrics will induce semantic distraction effects on reading comprehension performance. Our first hypothesis was that the accuracy rates in music conditions would be significantly lower than the accuracy rates with no music for college students (H1).

The impact of background music on reading comprehension is generally contingent on multiple factors such as music types (instrumental or lyric music with various tempos, intensity, familiarity) ( Banbury et al., 2001 ; Hallam and Mac Donald, 2009 ). In addition to music types, previous studies have confirmed that the effects of music on reading comprehension can be significantly different in various levels of individual diversity (e.g., personality and music preferences) or difficulty of the reading comprehension task ( Kiger, 1989 ; Kallinen, 2002 ; Anderson and Fuller, 2010 ). For example, Anderson and Fuller (2010) suggested that disruptive effects of background lyrical music on reading comprehension was more pronounced for 7th- and 8th-grade students exhibiting a stronger preference for the lyrical music, compared with their performance in a quiet environment. Our experimental work focused on identifying interactive effects of music (pop music with L1/L2 lyrics), individual habits (e.g., listening to music in daily study) and tasks (L1/L2 written texts), which helps test whether interference-by-process and a specific attentional capture occurs.

First, pop music is the preferred music genre for most college students ( Etaugh and Michals, 1975 ; Wang and Wang, 2015 ). For example, Wang and Wang (2015) surveyed 3,688 Chinese college students in Beijing, Inner Mongolia, Shanghai, Henan and Jiangxi regions of Mainland China, and found that: (1) the proportion of college students who liked pop music was as high as 65.05%; (2) 35.23% college students chose “love” as their favorite pop music theme comparing with themes “nostalgic” 33.21%, “witty/humorous” 14.27%, “alternative” 9.49%,“other” 15.73%; (3) 47.85% college student’ favorite singers are from “Hong Kong and Taiwan.” Thus, we choose a masterpiece of classic Mandarin pop music “The Goodbye Kiss” (sung by Jacky Cheung) as the music. Although the song was released in 1993, from its release to 2020, there have been covers of the song by well-known singers almost every year. Specially, this song was covered by Michael Learns to Rock (MLTR) in 2004, and the English version of this song “Take me to your heart” became a classic of international music. Comparing the lyrics of the two songs, the Mandarin lyrics of “The Goodbye Kiss” have a total of 52 sentences, and the whole song is divided into two subsections. The shortest sentence in Mandarin lyrics has a total of five Chinese words, and the longest sentence has 19 words; the English lyrics reproduce the characteristics of the original Chinese sentence well in terms of sentence length and neatness, the shortest sentence consists of four words, and the longest is only 10 words ( Wei, 2012 ). Thus, we chose the pop music with lyrics “The Goodbye Kiss” as our vocal music.

Second, Mandarin Chinese (L1) and English (L2) are the top 2 most spoken languages in the world, and belong to two different language families ( Ethnologue, n.d. ). Additionally, all Chinese students begin their English study in their third year of primary school or even earlier, and studying English is a key subject for the Chinese college entrance examination required for admission to the university. They will continue to study English to pass College English Test Band 4/6 (CET- 4/6, essential English exams for Chinese college students) in college, and have considerable exposure to English music. English is the most important and widely studied second language for most Chinese college students. Hence, we chose Chinse college students from Mainland China who learn English as a second language for the experiment. Based on the duplex-mechanism account of auditory distraction, when a similar process is used purposefully to accomplish a focal cognitive task and the involuntary processing of sound competes with it, interference-by-process occurs ( Hughes, 2014 ). In our experiment, interference-by-process is produced when lyrics are presented to college students who are deliberately completing a focal reading comprehension task, especially when the lyrics language is the same as the text language in the reading comprehension tasks. That is, the semantic activation of lyrics competes with the semantic access of reading comprehension tasks with the same language as lyrics. Thus, our hypothesis is that Chinese/English reading comprehension accuracy rates when listening to music in the same language would be significantly lower than that in different languages or no music (H2). To be specific, we hypothesized that Chinese reading comprehension accuracy rates when listening to music with Mandarin lyrics would be significantly lower than when listening to music with English lyrics, and English reading comprehension accuracy rates when listening to English music would be significantly lower than when listening to Mandarin music.

Third, students frequently report that listening to music while studying is useful ( Etaugh and Ptasnik, 1982 ), and these students are more likely to form the habit of listening to music in daily study. However, students without the habit instinctively think that music listening can provide a distraction that might affect reading comprehension. Individual differences in inhibitory control may exist between two groups. Inhibitory control refers to the ability to suppress an inappropriate reaction or disregard distracting or irrelevant information, and increased inhibitory control in students probably makes it easier for them to ignore distractions in their surroundings and concentrate on tasks inside and outside of the classroom ( Privitera et al., 2022b ). However, non-listeners do not develop the habit of listening to music while studying, probably because they have a low level of inhibitory control to concentrate on the focal tasks. Thus, we hypothesized that college students who typically did not report listening to music during study (non-listeners) would have lower reading comprehension accuracy rates than listeners when music was present (H3).

Based on the duplex-mechanism account of auditory distraction, regardless of the quality of target tasks (e.g., Chinese/English comprehension), auditory attentional capture happens whenever a sound produces a disengagement from tasks. Numerous sound varieties (e.g., one’s own name, or her own infant’s screams for a mother) have abilities to specifically captivate attention ( Hughes, 2014 ). Native language (Mandarin Chinese) is familiar and highly dominant, and may cause a specific attentional capture. We expect that both non-listeners and listeners may be more susceptible to auditory distraction when Mandarin music is present rather than English music. That is, in general, people’s ability to understand what they read was worse when they listened to music with native language compared to music in a second language or no music at all. Thus, for both non-listeners and listeners, we hypothesized that average reading comprehension accuracy rates (without distinction between Chinese and English) would be the lowest in the condition of Mandarin music compared with the English/no music condition (H4).

1.3 Research questions

In sum, it is worth examining the effects of different habits of listening to music on reading comprehension performance, which can help clarify whether cultivating habits of listening to music while studying is valuable or not. In addition, few studies used both lyrics languages and music-listening habits while study to explore distractive effects of music on reading comprehension. To solve this problem, in this paper, we designed an experiment to explore the effects of music type, written text language and listening habits on reading comprehension among Chinese college students. Our research questions are: (1) would the accuracy rates in music conditions be significantly lower than the accuracy rates with no music for college students? (2) would Chinese/English reading comprehension accuracy rates when listening to music in the same language be significantly lower than that in different languages or no music? (3) would non-listeners have lower L1 and L2 reading comprehension accuracy rates than listeners when music was present? (4) would average reading comprehension accuracy rates (without distinction between Chinese and English) be the lowest in the condition of Mandarin music compared with the English/no music condition?

2.1 Participants

Before the experiment, we calculated the minimum sample size of each group of participants using G*Power 3.1.9.7 software ( Faul et al., 2007 ) to reach the statistical power. For observing a similar effect to relevant studies ( Peng et al., 2017 ), we use Effect size f  = 0.22, ɑ = 0.05, 1-β = 0.8 as parameters, number of groups = 6, number of measurements = 2, non-sphericity correction = 1; under the F test of ANOVA: repeated measures, within-between interaction ( Faul et al., 2021 ). Hence the total minimum number of participants should be 72, and the minimum number of participants in each large group should be 36.

The participants were screened by filling out a researcher-designed questionnaire of background music listening habits. All participants were recruited randomly from Shandong Sport University in Shandong Province of Mainland China. A total of 90 participants (50 females) between 18 to 21 years of age (Mean = 19.14, SD = 0.92) were selected. Our experiment divided the participants into 2 large groups first: listeners (45 participants) and non-listeners (45 participants). Participants in each large group were randomly assigned to one of three groups: 15 Mandarin pop music group, 15 English pop music group and 15 no music group. All six groups of participants were assigned Chinese and English texts.

Participants were native Mandarin Chinese speakers who started learning English in the third grade of primary school. None of the participants were music majors and English majors, and none of the participants had any formal musical training. They were all right-handed with normal or corrected-to-normal vision. The experimental protocol was approved by the Research Ethics Committee of Shandong Sport University in China, and conducted in compliance with institutional guidelines and regulations. All participants signed an informed consent form prior to the experiment.

2.2 Experimental design

This study used a mixed factorial experimental design. There were two between-participants independent variables and a within-participants independent variable. The between-participants variables were listening habits (with two levels: listeners or non-listeners) and music type (with three levels: Mandarin pop music, English pop music or no music). The within-participants variable was text language (with two levels: Chinese or English). The dependent variable was accuracy rates for the reading comprehension tasks. Accuracy rates were defined as the mean percentage of the number of Chinese (English) reading comprehension items answered correctly in the total number of Chinese (English) reading comprehension items.

2.3 Materials and apparatus

Materials consisted of a questionnaire, pop music stimuli and written texts. The questionnaire was Researcher-designed Background Music Listening Habits Questionnaire, a self-report survey that was developed to assess participants’ habits of listening to music during study. This scale contained 15 items, each item rated on a Likert 5-point scale ranging from 1 to 5 (1 = Do not agree at all, 2 = Hardly agree, 3 = not sure, 4 = Mostly agree, 5 = Completely agree), and was scored as a continuous variable from 15 (minimum score) to 75 (maximum score). The Cronbach’s ɑ of the scale was 0.87. We used the questionnaire to screen listeners (a total score higher than 60, 60 is the average score of selecting option 4) and non-listeners (a total score lower than 30, 30 is the average score of selecting option 2) to examine distinct effects of listening habits on reading comprehension performance in the formal experiment.

Mandarin song “The Goodbye Kiss” (Mandarin name “Wen3 Bie2,” sung by Jacky Cheung) and English song “Take Me to Your Heart” (sung by Michael Learns to Rock) were used as background music stimuli, as these two songs have the same rhythm and tempo. The two songs were once popular music that are familiar to most Chinese college students. We used a music editor software Adobe Audition CS6 (Adobe Systems Inc., San Jose, CA, United States) to delete the blank space of “The Goodbye Kiss,” and the part with lyrics was kept to ensure that the participants could always be in a music environment with lyrics while carrying out reading comprehension tasks.

Chinese texts (300 character for each text) were selected from simulated tests of the College Entrance Examination; these texts are all about science and technology. English texts (150 words for each text) about education were selected from Public English Test System 3 (PET-3) tests. Preliminary tests were conducted on 120 college students, and finally 7 Chinese texts (coefficient of difficulty between 0.81 and 0.87) and 7 English texts (coefficient of difficulty between 0.85 and 0.90) were selected. There are no significant differences in difficulty coefficient of the 14 written texts. The difficulty coefficient of each text was estimated by the mean number of correct answers/4 (total number of questions). The coefficient of difficulty 0.81 indicates that, on average, three questions were correctly answered by college students. Participants read passages that were two paragraphs long, and then answered four true or false items following each passage. The items include both literal and inferential comprehension questions. Answers to literal questions involve facts such as who, when, where and what, and they can always be found in the texts. For example, “As early as 1909, Max Mow confirmed that there are some cells in the blood that can make blood, True or False.” For inferential questions, participants are required to determine a text’s meaning indirectly by using the information provided in the text. For example, “By the time most students graduate from high school, they spend less time watching TV than they do in class, True or False.” 3 Chinese texts and 3 English texts were used for assessing the levels of reading comprehension of all three groups (L1 pop music, L2 pop music and no music) of participants before the formal experiments. This was done to make sure that there were no significant differences of Chinese and English reading comprehension levels among the three groups. A different set of 3 Chinese texts and 3 English texts were used for the formal experiments. A Chinese text (difficulty coefficient 0.84) and an English text (difficulty coefficient 0.90) were selected for use in the practice phase.

The apparatus consisted of Lenovo laptops (Yoga 14 s, Lenovo Group Ltd., Beijing, China), noise-canceling headphones (SONY WH-1000XM3, Sony Corp., Tokyo, Japan) and E-prime 2.0. The music stimuli, instructions, texts and questions were all presented on Lenovo laptops using programs written in E-prime 2.0 (Psychology Software Tools, Pittsburgh, PA, United States) ( Schneider et al., 2012a , b ).

2.4 Procedure

Participants filled out the informed consent for participating in the study, then were screened by filling out the Questionnaire of Background Music Listening Habits online. Based on the questionnaire total score, the participants were divided into two large group: listeners and non-listeners. Participants in each large group were randomly assigned to one of three groups (Mandarin music, English music and no music). All three groups of participants completed Chinese and English reading comprehension tasks without music before formal experiments, and no significant differences of Chinese and English reading comprehension performance were observed among the three groups.

In the formal experiment phase, all participants were asked to complete experiment tasks in a quiet lab, with 10 participants in each group seated at individual tables with Lenovo laptops and headphones. First, participants were told to put on headphones and conduct the experiment on Lenovo laptops individually. All music was played between 60 dB ~ 65 dB(A), each participant first put on the headphones and checked to see whether the playback function of the headphones was normal. Then, Participants completed Chinese and English reading comprehension test items under each condition of music type. For each condition, half of the participants read the Chinese text first and the other half read the English text first. The 3 Chinese texts and 3 English texts were presented to participants randomly. After reading each passage, participants pressed the spacebar to end the reading (The maximum reading time for each text is 5 min), and proceeded to answer comprehension questions by pressing “T” (indicating truth) or “F” (indicating false) on keyboards. The flow chart of the experimental procedure presented using E-prime 2.0 was shown in Figure 1 .

Figure 1 . The flow chart of the experimental procedure presented using E-prime 2.0.

Participants were asked to answer questions as accurately as possible after reading the passages and to ignore the music. The accuracy rate of each participant was calculated by the total number of Chinese/English items answered correctly/12 (the total number of Chinese/English reading comprehension items). Every participant completed both Chinese texts and English texts in one of three conditions (Mandarin Chinese pop music, English pop music and no music). We tested the effects of listening to music in the same language conditions (L1 music + L1 texts, L2 music + L2 texts) or different language conditions (L1 music + L2 texts, L2 music + L1 texts). For example, participants listening to L1 (Mandarin Chinese) pop music completed L1 (Chinese) texts (the same as lyrics language) and L2 (English) texts (different from lyrics language). Music was played until all participants finished reading comprehension test items.

2.5 Statistical analyses

The Statistical Package for the Social Sciences (IBM SPSS, version 23.0; IBM SPSS, Armonk, NY, United States) was used for analysis of the data. The assumptions of ANOVA (homogeneity of variances and normal distribution) were tested. Then the reading comprehension accuracy rates were analyzed using a three-way mixed ANOVA with a within-participants factor (two types of written text language) and two between-participant variables (listening habits and music type). The alpha criterion was set to 0.05. Bonferroni correction was carried out for all post hoc analyses.

One-way ANOVA revealed that baseline reading comprehension performances of three groups (Mandarin music group, English music group and no music group) have no significant difference [Chinese: F (2, 87) = 0.226, p  = 0.718; English: F (2, 87) = 0.217, p  = 0.806].

3.1 Descriptive statistics

Means and standard deviations of the reading comprehension accuracy rates are shown in Table 1 . A three-way mixed ANOVA for reading comprehension accuracy rates, including two between-participants factors (2 listening habit, 3 music type) and one within-participants factor (2 written text language) was performed ( Table 2 ).

Table 1 . Reading comprehension accuracy rates [mean (standard deviations)] by group and condition.

Table 2 . A three-way analysis of variance (ANOVA) of reading comprehension accuracy rates.

3.2 Main effect analysis and interactive effect analyses

3.2.1 main effects of music type.

We tested our hypothesis (H1) that the accuracy rates in music conditions would be significantly lower than the accuracy rates with no music for college students. We performed a three-way mixed ANOVA for reading comprehension accuracy rates to obtain the main effects and interactive effects. Significant main effects of music type [ F (2, 87) = 232.791, p < 0.001, η 2 p = 0.847] were observed as shown in Table 2 . Post hoc analyses revealed the accuracy rates in Mandarin and English music conditions are significantly lower than the accuracy rates with no music ( ps < 0.01). A mean difference of accuracy rates was −0.081 between Mandarin music and English music condition (95% CI: [−0.110, −0.051]), and was −0.175 between English music and no music condition (95% CI: [−0.205, −0.145]). Thus, the results confirmed our hypothesis H1. The result reveals that music with lyrics decreased reading comprehension performance as compared to no music.

3.2.2 Interactive effects of music type and text language

Our second hypothesis (H2) was confirmed by using a three-way mixed ANOVA. H2 was that Chinese/English reading comprehension accuracy rates when listening to music in the same language would be significantly lower than those with different languages. We observed a significant interaction between music type and text language [ F (2, 87) = 113.829, p < 0.001, η 2 p = 0.730] as shown in Table 2 . For Chinese reading comprehension, as shown in Figure 2 , post hoc analyses showed that the accuracy rates in Mandarin music group were significantly lower than English music group [ t (58) = −5.526, p < 0.001] and no music group [ t (58) = −8.420, p < 0.001]. A mean difference of Chinese reading accuracy rates was −0.286 between Mandarin music and English music condition (95% CI: [−0.392, −0.180]), and was −0.378 between Mandarin music and no music condition (95% CI: [−0.484, −0.272]). For English reading comprehension, the accuracy rates in the English music group were significantly lower than the Mandarin music group [ t (58) = −2.385, p = 0.023 < 0.05; Figure 2 ] and the no music group [ t (58) = −7.041, p < 0.001; Figure 2 ]. A mean difference of English reading accuracy rates was −0.125 between English music and Mandarin music condition (95% CI: [−0.234, −0.016]), and was −0.258 between English music and no music condition (95% CI: [−0.367, −0.150]). These results confirmed our hypothesis H2, and suggested that college students were more distracted by music in the same language as the written texts.

Figure 2 . Accuracy rates of Chinese reading comprehension and English reading comprehension for different music types. ** p  < 0.01; *** p  < 0.001.

3.2.3 Main effects of listening habits and interactive effects of listening habits and music type

Three-way mixed ANOVA was also used to test our third hypothesis (H3) that non-listeners would have lower reading comprehension accuracy rates than listeners when music was present. The results in Table 2 showed that a significant main effect of listening habits [ F (1, 88) = 634.331, p < 0.001, η 2 p = 0.883]. Post hoc analyses revealed that reading comprehension accuracy rates were lower in non-listeners than listeners ( p < 0.001). The Table 2 also showed that the interactive effects of listening habits and music type were significant [ F (2, 87) = 160.672, p < 0.001, η 2 p = 0.793]. Post hoc analyses showed significantly lower reading comprehension accuracy rates in the non-listeners compared to listeners, in conditions of music as shown in Figure 3 [Mandarin music: t (58) = −138.782, p < 0.001; English music: t (58) = −99.729, p < 0.001]. A mean difference of accuracy rates between non-listeners and listeners was −0.430 in the Mandarin music condition (95% CI: [−0.464, −0.396]), and was −0.309 in the English music condition (95% CI: [−0.343, −0.274]). These results suggest that reading comprehension performance was more negatively affected by music in the non-listeners than in the listeners, confirming our third hypothesis (H3).

Figure 3 . Reading comprehension accuracy rates in different music type groups for different listening habits. *** p  < 0.001.

Significant interaction effects between listening habits and music type [ F (2, 87) = 160.672, p < 0.001, η 2 p = 0.793] were observed as shown in Table 2 . For the non-listeners, as shown in Figure 4 , post hoc analyses revealed the accuracy rates while listening to Mandarin music are significantly lower than with English music [ t (58) = −45.508, p  < 0.001] and significantly lower than accuracy rates with no music [ t (58) = −150.401, p < 0.001]. A mean difference of reading accuracy rates was −0.142 between Mandarin music and English music condition (95% CI: [−0.183, −0.100]), and was −0.467 between Mandarin music and no music condition (95% CI: [−0.508, −0.425]); For the listener, post hoc analyses revealed the accuracy rates while listening to Mandarin music are significantly lower than accuracy rates with no music [ t (58) = −14.524, p < 0.001]. A mean difference of reading accuracy rates was −0.045 between Mandarin music and no music condition (95% CI: [−0.086, −0.003]). Thus, the results also supported our hypothesis H4 that average reading comprehension accuracy rates (without distinction between Chinese and English) would be the lowest in the condition of Mandarin music compared with the English/no music condition for both non-listeners and listeners. These results suggested that music with native language lyrics negatively affected the reading comprehension performance of college students.

Figure 4 . Reading comprehension accuracy rates in different listening habits groups for different music types. * p  < 0.05; *** p  < 0.001.

4 Discussion

The main purpose of this study was to explore the disruptive effects of background music lyrics on first language (L1) and second language (L2) reading comprehension performance among Chinese college students. We also included the influence of music-listening habits by using a 3-factor mixed factorial experimental design. First, our results showed that reading comprehension accuracy rates in music conditions are significantly lower than the accuracy rates with no music. Second, L1/L2 reading comprehension accuracy rates when listening to music in the same language are significantly lower than when listening to a different language. Third, the results showed that significantly lower accuracy rates in non-listeners than listeners when music was played. Finally, for both the non-listeners and listeners, average reading comprehension accuracy rates are the lowest in the condition of Mandarin music compared with English/no music condition. Our results provide experimental evidence in support of distraction effects of L1 or L2 music on L1 and L2 reading comprehension performance among Chinese college students. In addition, our findings also offer additional evidence in favor of the duplex-mechanism account of auditory distraction. Overall, the results support our hypotheses.

4.1 The effect of music type

Compared to the no music condition, reading comprehension performance were reduced by music with lyrics. This result is consistent with previous studies which found disruptive effects of vocal music on reading comprehension ( Anderson and Fuller, 2010 ; Perham and Currie, 2014 ; Ren and Xu, 2019 ; Dong et al., 2022 ). Thompson et al. (2012) showed that fast and loud instrumental music disrupts reading comprehension more than slow-tempo music ( Thompson et al., 2012 ). However, though the music in our study is slow-tempo, disruptive effects on reading comprehension were still observed. Lyrics had a significantly detrimental effect on reading comprehension. The finding of the current study supports the interference-by-process in the duplex-mechanism account of auditory distraction. According to the interference-by-process, music with lyrics in both L1 and L2 detracted from the performance because semantically processing of the lyrics in these two languages conflicts with semantic processing and access that reading demands ( Quan and Kuo, 2023 ). For comparison, some researchers used musical excerpts in combination with meaningless words as music stimuli. The musical excerpts with meaningless lyrics were unknown to the participants to avoid any associations between the music and semantic or episodic memory. Their results showed neither an enhancing nor a detrimental effect on verbal learning when different styles of background music were played ( Jäncke and Sandmann, 2010 ). However, the present study indicated that music with meaningful lyrics interferes with reading comprehension performance. Language comprehension plays an important role in reading comprehension performance ( Hoover and Gough, 1990 ), and both lyrics and written texts contained semantic information. According to the duplex-mechanism account, from the perspective of the interference-by-process, the semantic interference effects can be explained by assuming that semantic speech triggers automatic spreading of semantic activation over a long-term semantic network that interferes with the analogous process of steering such networks for the purpose of retrieval in the reading comprehension tasks ( Marsh and Jones, 2010 ; Hughes, 2014 ). Therefore, the lyrics act as competing stimuli with written texts and impair their access to word meaning.

4.2 The interaction between music type and text language

Regardless of whether the music and texts were in their L1 or L2 language, Chinese college students were more distracted by music in the same language as the texts. This result indicates that a more detrimental effect on reading comprehension occurred when the auditory input (music lyrics) is the same as the written text language. Based on interference-by-process, the irrelevant semantic information from the speech creates competition for the primary tasks’ dynamic semantic encoding and retrieval processes. As they both vie for semantic access, impairment can therefore be explained in terms of a relative difficulty in choosing the appropriate source of semantic information ( Marsh et al., 2009 ). When lyrics language is the same as the text, the competition process becomes stronger and thus the selection process is more difficult, which causes a more disruptive effect on reading performance. We used music lyrics with L1/L2 as different potential sources of auditory distraction, and the finding provides a further strand of support for interference-by-process.

4.3 The effect of listening habits

Our results revealed that reading comprehension performance by the non-listeners were more negatively affected by music than the listeners. These findings are in line with the results of previous studies which showed that people who seldom studied in the presence of background music performed better on reading comprehension tasks in silence ( Etaugh and Michals, 1975 ; Etaugh and Ptasnik, 1982 ). These results indicate that background music caused detrimental effects for individuals who normally study without music. In contrast, college students who regularly listen to music while studying have much experience of listening to music, and the top-down features (e.g., high working memory and high inhibitory control) can lessen the interference to cognitive activities caused by shared processing of irrelevant information ( Quan and Kuo, 2023 ; Privitera et al., 2023b ). Specifically, differences in working memory/inhibitory control between non-listeners and listeners may lead the differential effects of music on reading comprehension, because working memory may generally have an impact on individual ability to carry out cognitive tasks while listening to music ( König et al., 2005 ; Christopher and Shelton, 2017 ), and it is generally observed that those with high working memory capacity are less easily distracted by irrelevant stimuli ( Hughes, 2014 ). Recent studies also revealed that differences in inhibitory and/or attentional control could predict academic performance including reading (e.g., Privitera et al., 2023b ), thus, the relatively low working memory/inhibitory control may make non-listeners were more disrupted by music compared with listeners. In other words, though listeners are negatively affected by music, they are accustomed to reading in the presence of music, thus background music sounds are less distracting for them.

4.4 The interaction between listening habits and music type

Our results indicated that for both non-listeners and listeners, music with native language lyrics negatively affected the average reading comprehension performance. The results provide support for the duplex-mechanism account of auditory distraction: in addition to interference-by-process, sound can also produce unnecessary distraction by attentional capture. Music lyrics with the same language as the written texts distract college students by interfering specifically with the similar semantic access processes involved in the reading comprehension task. In contrast, music with native language lyrics disengages students from reading comprehension tasks. Compared to L2 lyrics, native language lyrics are high dominant and more familiar, which may make students rely too much on music rather than keeping them from reading due to music. Thus, a specific attentional capture also caused the auditory distraction. This finding of auditory distraction in different lyrics language conditions provides additional evidence in favor of the duplex-mechanism account.

4.5 Limitations and further research

Several limitations should be noted. First, the participants’ English language proficiency, cognitive control and working memory were not assessed. In future study the L2 proficiency can be balanced to explore unique music lyrics effects on reading comprehension, because recent studies have shown that L2 proficiency are correlated to inhibition and attentional control ( Privitera et al., 2022a , 2023a ), and cognitive control has been found to have a significant impact on academic performance including reading ( Privitera et al., 2023b ). Working memory/cognitive control can be included as a key variable to explore its effect on reading comprehension while listening to music among non-listeners/listeners. Second, sound without lyrics (e.g., pop music without lyrics or white noise) was not included as one level of music type. Future study can compare reading comprehension performance differences between sound without lyrics group and music with lyrics/no music group to explore the various effects of sound. Third, questions about what music genres participants listen to and their relative frequencies were not included in the researcher-designed questionnaire of background music listening habits. The questionnaire needs to be modified, and should include questions on music genres in future study. Fourth, music type should be manipulated as a within-subject factor instead of a between-subject factor in future study. Finally, this is a behavioral experiment examining music lyrics effects on reading comprehension. With the aim of obtaining the brain and neuroscience evidence to support the duplex-mechanism account of auditory distraction, future studies could explore differences in brain and neural activities when students complete reading comprehension while listening to L1/L2 music, and identify the precise locus of the interference-by-process and attentional capture. These differences may indicate that interference-by-process and attentional capture obtain the functional support of different brain regions which further supports duplex-mechanism account of auditory distraction.

4.6 Implications

The current study benefits from several strengths. It is the first study to explore effects of L1 or L2 music lyrics on L1/L2 reading comprehension performance among Chinese college students with different listening habits. For reading comprehension with L1/L2, L1/L2 reading comprehension performance reduced more when the music lyrics language was the same as the written texts. For example, L2 reading performance decreased more when both lyrics and written texts language is L2. In general, for average reading comprehension performance, music with native language lyrics affected it negatively more than L2 music/no music. The current study provided experimental evidence to support the duplex-mechanism account of auditory distraction, and revealed that the duplex-mechanism account can also be applied to auditory distraction of reading comprehension tasks other than serial short-term tasks. The novelty of our study is to distinguish effects of lyrics with native language/s language on L1/L2 reading comprehension. Reading performance difference in lyrics with L1/L2 conditions suggests that auditory distraction has two functionally distinct forms: interference-by-process and attentional capture. The contribution of our research is that choosing music and written texts with L1/L2 helps methodically separate the potential individual contributions of interference-by-process and attentional capture to the overall disruption of task performance.

Our other findings were that reading comprehension performance was reduced by pop music lyrics. In addition, non-listeners were more distracted by lyrics than listeners. These findings have practical implications. Though most college students love pop music, and they usually report that listening to music while studying is beneficial, for college students and educators, it is better not to play pop music with lyrics while students, especially students without music-listening habits, are reading articles whether in their native languages or a second language.

5 Conclusion

The present study is an important first step in examining the effects of music with L1 or L2 lyrics on L1/L2 reading comprehension performance among Chinese college students with different listening habits. By using a 3-factor mixed factorial experimental design, we showed that the results verified our hypotheses. Specifically, the key findings are: (1) reading comprehension performance was negatively affected by music with lyrics compared to the no music condition; (2) L1/L2 reading comprehension was more affected by music in the same language as the texts; (3) Non-listeners were more negatively affected by music with lyrics than listeners; (4) For both non-listener and listeners, average reading comprehension accuracy rates are the lowest in the condition of music with native language lyrics. These findings support the claim that college students’ reading performance suffers when they listen to pop music with lyrics compared to no music, and provide experimental evidence support for the duplex-mechanism account of auditory distraction.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by Research Ethics Committee of Shandong Sport University. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

YS: Conceptualization, Data curation, Methodology, Supervision, Writing – original draft, Writing – review & editing. CS: Funding acquisition, Writing – original draft, Writing – review & editing. CL: Methodology, Writing – review & editing. XS: Investigation, Writing – review & editing. QL: Investigation, Writing – review & editing. HL: Methodology, Writing – review & editing.

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by Shandong University undergraduate teaching reform (grant numbers: 2023Y251; 2023YJJGND07) and undergraduate teaching reform in Shandong province (grant number: Z2022096).

Acknowledgments

We would like to thank Pamela Holt for useful discussions and critically reading the manuscript.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Anderson, S. A., and Fuller, G. B. (2010). Effect of music on reading comprehension of junior high school students. Sch. Psychol. 25, 178–187. doi: 10.1037/a0021213

Crossref Full Text | Google Scholar

Astolfi, A., Puglisi, G. E., Murgia, S., Minelli, G., Pellerey, F., Prato, A., et al. (2019). Influence of classroom acoustics on noise disturbance and well-being for first graders. Front. Psychol. 10:2736. doi: 10.3389/fpsyg.2019.02736

PubMed Abstract | Crossref Full Text | Google Scholar

Banbury, S. P., Macken, W. J., Tremblay, S., and Jones, D. M. (2001). Auditory distraction and short-term memory: phenomena and practical implications. Hum. Factors 43, 12–29. doi: 10.1518/001872001775992462

Calderwood, C., Ackerman, P. L., and Conklin, E. M. (2014). What else do college students “do” while studying? An investigation of multitasking. Comput. Educ. 75, 19–29. doi: 10.1016/j.compedu.2014.02.004

Carlson, J. K., Hoffman, J., Gray, D., and Thompson, A. (2004). A musical interlude: using music and relaxation to improve reading performance. Interv. Sch. Clin. 39, 246–250. doi: 10.1177/10534512040390040801

Christopher, E. A., and Shelton, J. T. (2017). Individual differences in working memory predict the effect of music on student performance. J. Appl. Res. Mem. Cogn. 6, 167–173. doi: 10.1016/j.jarmac.2017.01.012

Dong, Y., Zheng, H. Y., Wu, S. X. Y., Huang, F. Y., Peng, S. N., Sun, S. Y. K., et al. (2022). The effect of Chinese pop background music on Chinese poetry reading comprehension. Psychol. Music 50, 1544–1565. doi: 10.1177/03057356211062940

Du, M., Jiang, J., Li, Z. M., Man, D. R., and Jiang, C. M. (2020). The effects of background music on neural responses during reading comprehension. Sci. Rep. 10:18651. doi: 10.1038/s41598-020-75623-3

Eimer, M., Nattkemper, D., Schröger, E., and Prinz, W. (1996). “Involuntary attention” in Handbook of perception and action . eds. O. Neumann and A. F. Sanders, vol. 3 (London: Academic Press), 389–446.

Google Scholar

Erten, O., Ece, A. S., and Eren, A. (2015). The effects of reading with music on reading comprehension. Glob. J. Hum. Soc. Sci. 1, 619–627.

Etaugh, C., and Michals, D. (1975). Effects on reading comprehension of preferred music and frequency of studying to music. Percept. Mot. Skills 41, 553–554. doi: 10.2466/pms.1975.41.2.553

Etaugh, C., and Ptasnik, P. (1982). Effects of studying to music and post-study relaxation on reading comprehension. Percept. Mot. Skills 55, 141–142. doi: 10.2466/pms.1982.55.1.141

Ethnologue . (n.d.). Languages of the World . SIL International. Available at: https://www.ethnologue.com/ (Accessed February 27, 2024).

Faul, F., Erdfelder, E., Lang, A.-G., and Buchner, A. (2007). G*power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav. Res. Methods 39, 175–191. doi: 10.3758/BF03193146

Faul, F., Erdfelder, E., Lang, A.-G., and Buchner, A. (2021). F test: Fixed effects ANOVA–- special, main effects and interactions. G * Power 3.1 manual. 28–29. Available at: https://www.psychologie.hhu.de/arbeitsgruppen/allgemeine-psychologie-und-arbeitspsychologie/gpower .

Furnham, A., and Strbac, L. (2002). Music is as distracting as noise: the differential distraction of background music and noise on the cognitive test performance of introverts and extraverts. Ergonomics 45, 203–217. doi: 10.1080/00140130210121932

Hallam, S., and Mac Donald, R. A. R. (2009). “The effects of music in community and educational settings” in The Oxford handbook of music psychology (New York: Oxford University Press), 471–480.

Hoover, W. A., and Gough, P. B. (1990). The simple view of reading. Read. Writ. 2, 127–160. doi: 10.1007/BF00401799

Hughes, R. W. (2014). Auditory distraction: a duplex-mechanism account. PsyCh 3, 30–41. doi: 10.1002/pchj.44

Jäncke, L., and Sandmann, P. (2010). Music listening while you learn: no influence of background music on verbal learning. Behav. Brain Funct. 6:3. doi: 10.1186/1744-9081-6-3

Kallinen, K. (2002). Reading news from a pocket computer in a distracting environment: effects of the tempo of background music. Comput. Hum. Behav. 18, 537–551. doi: 10.1016/S0747-5632(02)00005-5

Kämpfe, J., Sedlmeier, P., and Renkewitz, F. (2010). The impact of background music on adult listeners: a meta-analysis. Psychol. Music 39, 424–448. doi: 10.1177/0305735610376261

Kang, H. J., and Williamson, V. J. (2012). The effect of background music on second language learning. In Proceedings of the 12th International Conference on Music Perception and Cognition and the 8th Triennial Conference of the European Society for the Cognitive Sciences of Music, pp. 516–518.

Khaghaninejad, M. S., Motlagh, H. S., and Chamacham, R. (2016). How does Mozart’s music affect the reading comprehension of Iranian EFL learners of both genders? Int. J. Human. Cult. Stud. 489–499.

Kiger, D. M. (1989). Effects of music information load on a reading comprehension task. Percept. Mot. Skills 69, 531–534. doi: 10.2466/pms.1989.69.2.531

König, C. J., Bühner, M., and Mürling, G. (2005). Working memory, fluid intelligence, and attention are predictors of multitasking performance, but polychronicity and extraversion are not. Hum. Perform. 18, 243–266. doi: 10.1207/s15327043hup1803_3

Marsh, J. E., Hughes, R. W., and Jones, D. M. (2008). Auditory distraction in semantic memory: a process-based approach. J. Mem. Lang. 58, 682–700. doi: 10.1016/j.jml.2007.05.002

Marsh, J. E., Hughes, R. W., and Jones, D. M. (2009). Interference by process, not content, determines semantic auditory distraction. Cognition 110, 23–38. doi: 10.1016/j.cognition.2008.08.003

Marsh, J. E., and Jones, D. M. (2010). Cross-modal distraction by background speech: what role for meaning? Noise Health 12, 210–216. doi: 10.4103/1463-1741.70499

Martin, R. C., Wogalter, M. S., and Forlano, J. G. (1988). Reading comprehension in the presence of unattended speech and music. J. Mem. Lang. 27, 382–398. doi: 10.1016/0749-596X(88)90063-0

Oswald, C. J. P., Tremblay, S., and Jones, D. M. (2000). Disruption of comprehension by the meaning of irrelevant sound. Memory 8, 345–350. doi: 10.1080/09658210050117762

Peng, S. N., Chen, M. J., and Wang, J. D. (2017). Background music promotes reading comprehension: experimental results with different preferences. J. Jiaying Univ. 10, 96–100.

Perfetti, C. A., Landi, N., and Oakhill, J. (2005) in The acquisition of Reading comprehension skill, the science of Reading: A handbook . eds. M. J. Snowling and C. Hulme (Oxford: Blackwell Publishing), 227–247.

Perham, N., and Currie, H. (2014). Does listening to preferred music improve reading comprehension performance? Appl. Cogn. Psychol. 28, 279–284. doi: 10.1002/acp.2994

Privitera, A. J., Momenian, M., and Weekes, B. S. (2022a). Task-specific bilingual effects in mandarin-English speaking high school students in China. Curr. Res. Behav. Sci. 3:100066. doi: 10.1016/j.crbeha.2022.100066

Privitera, A. J., Momenian, M., and Weekes, B. S. (2023a). Graded bilingual effects on attentional network function in Chinese high school students. Biling. Lang. Congn. 26, 527–537. doi: 10.1017/S1366728922000803

Privitera, A. J., Zhou, Y., and Xie, X. (2023b). Inhibitory control as a significant predictor of academic performance in Chinese high schoolers. Child Neuropsychol. 29, 457–473. doi: 10.1080/09297049.2022.2098941

Privitera, A. J., Zhou, Y., Xie, X., and Huang, D. (2022b). Inhibitory control predicts academic performance beyond fluid intelligence and processing speed in English-immersed Chinese high schoolers. Proceedings of the Annual Meeting of the Cognitive Science Society, 44. Available at: https://escholarship.org/uc/item/77r925hr .

Quan, Y., and Kuo, Y. L. (2023). The effects of Chinese and English background music on Chinese reading comprehension. Psychol. Music 51, 655–663. doi: 10.1177/03057356221101647

Ren, Y. N., and Xu, W. X. (2019). Effect of Chinese and English background music on efficiency on Chinese and English reading comprehension. Adv. Psychol. 9, 978–984. doi: 10.12677/AP.2019.96120

Schneider, W., Eschman, A., and Zuccolotto, A. (2012a). E-prime User’s guide . Pittsburgh: Psychology Software Tools, Inc.

Schneider, W., Eschman, A., and Zuccolotto, A. (2012b). E-Prime Reference Guide . Pittsburgh: Psychology Software Tools, Inc.

Thompson, W. F., Schellenberg, E. G., and Letnic, A. K. (2012). Fast and loud background music disrupts reading comprehension. Psychol. Music 40, 700–708. doi: 10.1177/0305735611400173

Wang, L. P., and Wang, F. (2015). An empirical study on popular songs and the cultivation of college students’ core values. J. Inner Mongolia Norm. Univ. Edu. Sci. 33–37.

Wei, S. H. (2012). Lyrics Translation under the Guidance of Xu Yuanchong’s Poetry Translation Theory: A Case Study of the English Translation of the Internet Pop Song “The Goodbye Kiss”. Campus English :113+115.

Zhang, H., Miller, K., Cleveland, R., and Cortina, K. (2018). How listening to music affects reading: evidence from eye tracking. J. Exp. Psychol. Learn. Mem. Cogn. 44, 1778–1791. doi: 10.1037/xlm0000544

Keywords: reading comprehension, study habits, pop music with lyrics, native language lyrics, second language lyrics, written text language, Chinese college students

Citation: Sun Y, Sun C, Li C, Shao X, Liu Q and Liu H (2024) Impact of background music on reading comprehension: influence of lyrics language and study habits. Front. Psychol . 15:1363562. doi: 10.3389/fpsyg.2024.1363562

Received: 13 January 2024; Accepted: 25 March 2024; Published: 05 April 2024.

Reviewed by:

Copyright © 2024 Sun, Sun, Li, Shao, Liu and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Chuanning Sun, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

• UNC Libraries
• Collections
• Creative Music Research in Special Collections
• Creative Music Research Examples and Methodologies

Creative Music Research in Special Collections: Creative Music Research Examples and Methodologies

• Archives and Libraries
• Using a Finding Aid
• Registering & Requesting Materials
• Primary Source Analysis
• Music Copyright
• Creative Research Opportunities

Types of Projects

Here are a few possible project directions for using archives and primary sources. This is not an exhaustive list – the possibilities are endless!

Conceptual inspiration

Is there a unique item or story that you want to expand upon? Perhaps there is a diary entry, a letter or an oral history that speaks to you.

Understanding Repertoire and Playing Styles

Primary sources offer unique insight into historical repertoire and playing styles. This could come in the form of a sound recording or a score. How does the playing style and/or repertoire differ from that of contemporary players?

Improvisation and Composition

Any type of primary source can serve as an inspiration for improvisation or composition. It could be a recording, a photograph, a silent film – what ways can different medias inspire improvisation and composition?

Sampling and Production

What public domain recordings are available in the archive? How can sampling an oral history or a music recording add to the production?

Program and Album notes

Primary sources can also be helpful when writing program or album notes. What historical perspectives or reflections of artists or communities can be represented in program and album notes?

Installations and Exhibits

Multi-media installations can be a compelling way to combine primary source media with other creative content.

Creative Research Methodologies

• A Guide to archives for artists and makers from Providence Public Library A guide to using archives for artists and makers in the form of a graphic novel. Created by artist and librarian Jeremy Ferris.
• A Guide to archives for artists and makers Downloadable PDF

• << Previous: Creative Research Opportunities
• Last Updated: Apr 15, 2024 10:30 AM
• URL: https://guides.lib.unc.edu/musicresearch

Search & Find

• E-Research by Discipline
• More Search & Find

Places & Spaces

• Places to Study
• Book a Study Room
• Printers, Scanners, & Computers
• More Places & Spaces
• Borrowing & Circulation
• Request a Title for Purchase
• Schedule Instruction Session
• More Services

Support & Guides

• Course Reserves
• Research Guides
• Citing & Writing
• More Support & Guides
• Mission Statement
• Diversity Statement
• Staff Directory
• Job Opportunities
• Give to the Libraries
• News & Exhibits
• Reckoning Initiative
• More About Us

• Search This Site
• Privacy Policy
• Accessibility
• Give Us Your Feedback
• 208 Raleigh Street CB #3916
• Chapel Hill, NC 27515-8890
• 919-962-1053

USask supports new music, community organizations

A unique research grant supports the creation of new compositions for a concert supporting an important cause.

USask Communications Apr 15, 2024

Funding from the University of Saskatchewan (USask) has sparked the creation of innovative artistic work for an organization with deep ties to the institution.  

With support from the Office of the Vice-President Research (OVPR), a concert took place on March 9 performed by the Saskatoon Jazz Orchestra (SJO) in support of the Ukrainian Museum of Canada.  

Dr. Baljit Singh (PhD), USask’s Vice-President Research, said research and creativity in the arts goes hand-in-hand and is of integral importance to USask’s research, scholarly and artistic work mission.  

“Artistic innovation is something to be celebrated by institutions like USask, and we need to continue fostering new artistic works in our community,” he said. “USask is home to some of the country’s most talented artists across many fields, and supporting their creativity makes the university a stronger and more diverse place.”  

The social justice-themed concert, titled A Kolomyika Fantasy , featured musicians from USask as well as many USask alumni and top professional musicians from across Western Canada. Some special compositions for the concert were also developed by USask faculty and alumni, delving into Ukrainian musical tradition as their muse.  

Dean McNeill, the artistic director of the SJO and the head of USask’s Department of Music, lauded USask for its support of the arts in the community.  

McNeill said it’s impressive to see how much more can be accomplished in the fine arts with funding initiatives like this. He said the SJO would likely not exist in its current form were it not for support from organizations like USask being involved in the artistic community in various ways.  

“Wearing both hats, as a faculty member and as artistic director of the SJO, does help me make these university/community connections,” McNeill said. “In this way I can often create win-win scenarios in which I’m able to forward some on my own artistic and research artistic aspirations as a faculty member and at the same time serve and develop the community in artistic and social justice-forward ways.”  

The concert also received support from other organizations in Saskatoon and across the country, including arts-focused groups SK Arts, the Saskatoon Symphony Orchestra and the Canada Council for the Arts.  

For McNeill, continuing to find avenues for the artistic community and USask to support each other is an exciting prospect to reflect and act on.  

“I think the university always has been and continues to be very interested in connective tissue that links its faculty, students, programs, and physical space to the various communities within which it resides,” McNeill said.  

“This concert was not only a fundraiser ... It is one of many examples of our fine arts faculty doing important work within the university and connecting said work out into the community in important, substantive and impactful ways.”  

This concert can be viewed on the Saskatoon Symphony Orchestra’s Concert Stream platform, with all proceeds from this concert supporting the Ukrainian Museum of Canada.  

Together, we will undertake the research the world needs. We invite you to join by  supporting critical research  at USask.

USask rises and expands success in QS international subject rankings

Grandparents inspire Indigenous Studies student at USask

‘There’s so much about a dog that touches people’s hearts’

USask announces 2024 Images of Research contest winners